logs/whisper-spoken-ner-small-pipe-lora.err

Process rank: 0, device: cuda:0, n_gpu: 1distributed training: True, 16-bits training: True
/users/spraak/qmeeus/micromamba/envs/torch-cu121/lib/python3.10/site-packages/transformers/configuration_utils.py:508: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
  warnings.warn(
[INFO|configuration_utils.py:737] 2024-01-08 18:44:38,532 >> loading configuration file configs/whisper_small_ner_mtl.json
[WARNING|configuration_utils.py:617] 2024-01-08 18:44:38,532 >> You are using a model of type whisper to instantiate a model of type whisper_for_slu. This is not supported for all configurations of models and can yield errors.
[INFO|configuration_utils.py:802] 2024-01-08 18:44:38,535 >> Model config WhisperSLUConfig {
  "_name_or_path": "openai/whisper-small",
  "activation_dropout": 0.0,
  "activation_function": "gelu",
  "adaptor_activation": "relu",
  "adaptor_init": "constant",
  "adaptor_layernorm": true,
  "apply_spec_augment": false,
  "architectures": [
    "WhisperForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "begin_suppress_tokens": [
    220,
    50257
  ],
  "bos_token_id": 50257,
  "classifier_proj_size": 256,
  "crf_transition_matrix": null,
  "d_model": 768,
  "decoder_attention_heads": 12,
  "decoder_ffn_dim": 3072,
  "decoder_layerdrop": 0.0,
  "decoder_layers": 12,
  "decoder_start_token_id": 50258,
  "dropout": 0.0,
  "encoder_attention_heads": 12,
  "encoder_ffn_dim": 3072,
  "encoder_layerdrop": 0.0,
  "encoder_layers": 12,
  "eos_token_id": 50257,
  "forced_decoder_ids": [
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  ],
  "init_std": 0.02,
  "is_encoder_decoder": true,
  "mask_feature_length": 10,
  "mask_feature_min_masks": 0,
  "mask_feature_prob": 0.0,
  "mask_time_length": 10,
  "mask_time_min_masks": 2,
  "mask_time_prob": 0.05,
  "max_length": 448,
  "max_source_positions": 1500,
  "max_target_positions": 448,
  "median_filter_width": 7,
  "model_type": "whisper_for_slu",
  "num_hidden_layers": 12,
  "num_mel_bins": 80,
  "pad_token_id": 50257,
  "scale_embedding": false,
  "slu_attention_heads": 12,
  "slu_dropout": 0.3,
  "slu_embed_dim": 768,
  "slu_ffn_dim": 2048,
  "slu_focus": 1.0,
  "slu_input_from": "decoder",
  "slu_input_layers": [
    11
  ],
  "slu_labels": null,
  "slu_layers": 2,
  "slu_max_positions": null,
  "slu_output_dim": 37,
  "slu_pad_token_id": 1,
  "slu_start_token_id": 36,
  "slu_task": "named_entity_recognition",
  "slu_weight": 0.2,
  "suppress_tokens": [
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  "task": "token_classification",
  "teacher": null,
  "torch_dtype": "float32",
  "transformers_version": "4.37.0.dev0",
  "use_cache": true,
  "use_crf": false,
  "use_weighted_layer_sum": false,
  "vocab_size": 51865
}

/users/spraak/qmeeus/micromamba/envs/torch-cu121/lib/python3.10/site-packages/transformers/models/auto/feature_extraction_auto.py:328: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
  warnings.warn(
[INFO|feature_extraction_utils.py:535] 2024-01-08 18:44:38,556 >> loading configuration file /esat/audioslave/qmeeus/exp/whisper_slu/train/whisper-small-spoken-ner/preprocessor_config.json
[INFO|feature_extraction_utils.py:579] 2024-01-08 18:44:38,563 >> Feature extractor WhisperFeatureExtractor {
  "chunk_length": 30,
  "feature_extractor_type": "WhisperFeatureExtractor",
  "feature_size": 80,
  "hop_length": 160,
  "n_fft": 400,
  "n_samples": 480000,
  "nb_max_frames": 3000,
  "padding_side": "right",
  "padding_value": 0.0,
  "processor_class": "WhisperProcessor",
  "return_attention_mask": false,
  "sampling_rate": 16000
}

/users/spraak/qmeeus/micromamba/envs/torch-cu121/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py:691: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
  warnings.warn(
[INFO|tokenization_utils_base.py:2024] 2024-01-08 18:44:38,630 >> loading file vocab.json
[INFO|tokenization_utils_base.py:2024] 2024-01-08 18:44:38,630 >> loading file tokenizer.json
[INFO|tokenization_utils_base.py:2024] 2024-01-08 18:44:38,630 >> loading file merges.txt
[INFO|tokenization_utils_base.py:2024] 2024-01-08 18:44:38,630 >> loading file normalizer.json
[INFO|tokenization_utils_base.py:2024] 2024-01-08 18:44:38,630 >> loading file added_tokens.json
[INFO|tokenization_utils_base.py:2024] 2024-01-08 18:44:38,631 >> loading file special_tokens_map.json
[INFO|tokenization_utils_base.py:2024] 2024-01-08 18:44:38,631 >> loading file tokenizer_config.json
[WARNING|logging.py:314] 2024-01-08 18:44:39,435 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
/users/spraak/qmeeus/micromamba/envs/torch-cu121/lib/python3.10/site-packages/transformers/modeling_utils.py:2790: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
  warnings.warn(
[INFO|modeling_utils.py:3373] 2024-01-08 18:44:39,454 >> loading weights file /esat/audioslave/qmeeus/exp/whisper_slu/train/whisper-small-spoken-ner/model.safetensors
[INFO|configuration_utils.py:826] 2024-01-08 18:44:41,796 >> Generate config GenerationConfig {
  "begin_suppress_tokens": [
    220,
    50257
  ],
  "bos_token_id": 50257,
  "decoder_start_token_id": 50258,
  "eos_token_id": 50257,
  "forced_decoder_ids": [
    [
      1,
      50259
    ],
    [
      2,
      50359
    ],
    [
      3,
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    ]
  ],
  "max_length": 448,
  "pad_token_id": 50257
}

[INFO|modeling_utils.py:4227] 2024-01-08 18:44:42,780 >> All model checkpoint weights were used when initializing WhisperSLU.

[INFO|modeling_utils.py:4235] 2024-01-08 18:44:42,780 >> All the weights of WhisperSLU were initialized from the model checkpoint at /esat/audioslave/qmeeus/exp/whisper_slu/train/whisper-small-spoken-ner.
If your task is similar to the task the model of the checkpoint was trained on, you can already use WhisperSLU for predictions without further training.
[INFO|configuration_utils.py:779] 2024-01-08 18:44:42,795 >> loading configuration file /esat/audioslave/qmeeus/exp/whisper_slu/train/whisper-small-spoken-ner/generation_config.json
[INFO|configuration_utils.py:826] 2024-01-08 18:44:42,796 >> Generate config GenerationConfig {
  "alignment_heads": [
    [
      5,
      3
    ],
    [
      5,
      9
    ],
    [
      8,
      0
    ],
    [
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    [
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    [
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    [
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    [
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    ]
  ],
  "begin_suppress_tokens": [
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  "bos_token_id": 50257,
  "decoder_start_token_id": 50258,
  "eos_token_id": 50257,
  "forced_decoder_ids": [
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  "is_multilingual": true,
  "lang_to_id": {
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trainable params: 2,111,784 || all params: 255,250,145 || trainable%: 0.8273390011198622
[INFO|feature_extraction_utils.py:425] 2024-01-08 18:44:47,327 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/preprocessor_config.json
[INFO|tokenization_utils_base.py:2432] 2024-01-08 18:44:47,357 >> tokenizer config file saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tokenizer_config.json
[INFO|tokenization_utils_base.py:2441] 2024-01-08 18:44:47,358 >> Special tokens file saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/special_tokens_map.json
[INFO|configuration_utils.py:483] 2024-01-08 18:44:47,419 >> Configuration saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/config.json
[INFO|trainer.py:522] 2024-01-08 18:44:50,691 >> max_steps is given, it will override any value given in num_train_epochs
[INFO|trainer.py:571] 2024-01-08 18:44:50,691 >> Using auto half precision backend
wandb: Currently logged in as: qmeeus. Use `wandb login --relogin` to force relogin
wandb: wandb version 0.16.1 is available!  To upgrade, please run:
wandb:  $ pip install wandb --upgrade
wandb: Tracking run with wandb version 0.15.12
wandb: Run data is saved locally in /usr/data/condor/execute/dir_314523/whisper_slu/wandb/run-20240108_184452-35ireexg
wandb: Run `wandb offline` to turn off syncing.
wandb: Syncing run run-2024-01-08_18-44-50
wandb: ⭐️ View project at https://wandb.ai/qmeeus/Whisper%20PEFT%20Fine-Tuning
wandb: 🚀 View run at https://wandb.ai/qmeeus/Whisper%20PEFT%20Fine-Tuning/runs/35ireexg
[INFO|trainer.py:718] 2024-01-08 18:44:53,398 >> The following columns in the training set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:1712] 2024-01-08 18:44:53,456 >> ***** Running training *****
[INFO|trainer.py:1713] 2024-01-08 18:44:53,456 >>   Num examples = 71,615
[INFO|trainer.py:1714] 2024-01-08 18:44:53,456 >>   Num Epochs = 9
[INFO|trainer.py:1715] 2024-01-08 18:44:53,456 >>   Instantaneous batch size per device = 4
[INFO|trainer.py:1718] 2024-01-08 18:44:53,456 >>   Total train batch size (w. parallel, distributed & accumulation) = 128
[INFO|trainer.py:1719] 2024-01-08 18:44:53,456 >>   Gradient Accumulation steps = 32
[INFO|trainer.py:1720] 2024-01-08 18:44:53,456 >>   Total optimization steps = 5,000
[INFO|trainer.py:1721] 2024-01-08 18:44:53,459 >>   Number of trainable parameters = 2,111,784
[INFO|integration_utils.py:722] 2024-01-08 18:44:53,462 >> Automatic Weights & Biases logging enabled, to disable set os.environ["WANDB_DISABLED"] = "true"
[WARNING|logging.py:314] 2024-01-08 18:44:53,481 >> You're using a WhisperTokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.
[INFO|trainer.py:718] 2024-01-08 19:13:47,119 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-08 19:19:31,366 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-200
[INFO|feature_extraction_utils.py:425] 2024-01-08 19:19:31,494 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-200/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-08 19:48:40,699 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-08 19:54:22,629 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-400
[INFO|feature_extraction_utils.py:425] 2024-01-08 19:54:22,697 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-400/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-08 20:23:52,708 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-08 20:29:34,863 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-600
[INFO|feature_extraction_utils.py:425] 2024-01-08 20:29:34,923 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-600/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-08 20:57:32,183 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-08 21:03:16,687 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-800
[INFO|feature_extraction_utils.py:425] 2024-01-08 21:03:16,748 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-800/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-08 21:31:12,469 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-08 21:36:50,658 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-1000
[INFO|feature_extraction_utils.py:425] 2024-01-08 21:36:50,723 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-1000/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-08 22:04:44,620 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-08 22:10:25,435 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-1200
[INFO|feature_extraction_utils.py:425] 2024-01-08 22:10:25,503 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-1200/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-08 22:38:14,532 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-08 22:43:55,646 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-1400
[INFO|feature_extraction_utils.py:425] 2024-01-08 22:43:55,713 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-1400/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-08 23:11:49,094 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-08 23:17:29,789 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-1600
[INFO|feature_extraction_utils.py:425] 2024-01-08 23:17:29,855 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-1600/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-08 23:45:21,350 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-08 23:50:59,797 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-1800
[INFO|feature_extraction_utils.py:425] 2024-01-08 23:50:59,864 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-1800/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-09 00:18:55,674 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-09 00:24:38,854 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-2000
[INFO|feature_extraction_utils.py:425] 2024-01-09 00:24:38,925 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-2000/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-09 00:52:30,504 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-09 00:58:08,825 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-2200
[INFO|feature_extraction_utils.py:425] 2024-01-09 00:58:08,891 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-2200/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-09 01:26:03,365 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-09 01:31:41,568 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-2400
[INFO|feature_extraction_utils.py:425] 2024-01-09 01:31:41,637 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-2400/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-09 01:59:37,802 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-09 02:05:15,416 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-2600
[INFO|feature_extraction_utils.py:425] 2024-01-09 02:05:15,487 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-2600/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-09 02:33:13,316 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-09 02:38:52,241 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-2800
[INFO|feature_extraction_utils.py:425] 2024-01-09 02:38:52,309 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-2800/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-09 03:06:54,838 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-09 03:12:32,446 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-3000
[INFO|feature_extraction_utils.py:425] 2024-01-09 03:12:32,518 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-3000/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-09 03:40:35,202 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-09 03:46:14,094 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-3200
[INFO|feature_extraction_utils.py:425] 2024-01-09 03:46:14,164 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-3200/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-09 04:14:09,998 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-09 04:19:47,911 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-3400
[INFO|feature_extraction_utils.py:425] 2024-01-09 04:19:47,978 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-3400/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-09 04:47:50,188 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-09 04:53:29,921 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-3600
[INFO|feature_extraction_utils.py:425] 2024-01-09 04:53:29,988 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-3600/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-09 05:21:33,159 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-09 05:27:11,558 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-3800
[INFO|feature_extraction_utils.py:425] 2024-01-09 05:27:11,628 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-3800/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-09 05:55:12,769 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-09 06:00:50,862 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-4000
[INFO|feature_extraction_utils.py:425] 2024-01-09 06:00:50,923 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-4000/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-09 06:28:50,219 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-09 06:34:27,483 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-4200
[INFO|feature_extraction_utils.py:425] 2024-01-09 06:34:27,548 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-4200/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-09 07:02:24,846 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-09 07:08:04,451 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-4400
[INFO|feature_extraction_utils.py:425] 2024-01-09 07:08:04,518 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-4400/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-09 07:36:02,929 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-09 07:41:42,554 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-4600
[INFO|feature_extraction_utils.py:425] 2024-01-09 07:41:42,623 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-4600/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-09 08:09:40,000 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-09 08:15:17,334 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-4800
[INFO|feature_extraction_utils.py:425] 2024-01-09 08:15:17,402 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-4800/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-09 08:43:18,208 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
[INFO|trainer.py:2895] 2024-01-09 08:48:55,880 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-5000
[INFO|feature_extraction_utils.py:425] 2024-01-09 08:48:55,951 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/tmp-checkpoint-5000/preprocessor_config.json
[INFO|trainer.py:1953] 2024-01-09 08:48:56,055 >> 

Training completed. Do not forget to share your model on huggingface.co/models =)


[INFO|trainer.py:2895] 2024-01-09 08:48:56,060 >> Saving model checkpoint to /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora
[INFO|feature_extraction_utils.py:425] 2024-01-09 08:48:56,146 >> Feature extractor saved in /esat/audioslave/qmeeus/exp/whisper_slu/pipeline/whisper-small-spoken-ner-lora/preprocessor_config.json
[INFO|trainer.py:718] 2024-01-09 08:48:56,152 >> The following columns in the evaluation set don't have a corresponding argument in `PeftModel.forward` and have been ignored: input_length. If input_length are not expected by `PeftModel.forward`,  you can safely ignore this message.
wandb: Waiting for W&B process to finish... (success).
wandb: 
wandb: Run history:
wandb:                  eval/f1_score ▁▁▄▅▄▅▅▅▅▆▆▆▇▇▇▇▆██▇▇█████
wandb:                  eval/label_f1 ▆▆▄▃▁▅▄▂▄█▆▅▆▅▆▄▄▅▆▆▆▆▃▄▄▄
wandb:                      eval/loss █▅▄▃▃▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁
wandb:                   eval/runtime █▆▆█▂▄▅▄▂▇▂▂▁▃▁▃▂▃▂▂▁▃▃▁▁▃
wandb:        eval/samples_per_second ▁▃▃▁▇▅▄▅▇▂▇▇█▆█▆▇▆▇▇█▆▆██▆
wandb:          eval/steps_per_second ▁▄▃▁▇▅▄▅▆▂▆▇▇▆▇▆▇▅▆▇█▅▅█▇▅
wandb:                       eval/wer █▅▆▅▂▂▂▃▁▃▁▁▁▃▃▂▃▃▃▃▃▃▃▃▃▃
wandb:                    train/epoch ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇████
wandb:              train/global_step ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇████
wandb:            train/learning_rate ████████▇▇▇▇▇▆▆▆▅▅▅▅▄▄▄▄▃▃▃▃▂▂▂▂▂▁▁▁▁▁▁▁
wandb:                     train/loss █▃▃▃▂▂▂▂▂▂▂▂▂▂▁▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁
wandb:               train/total_flos ▁
wandb:               train/train_loss ▁
wandb:            train/train_runtime ▁
wandb: train/train_samples_per_second ▁
wandb:   train/train_steps_per_second ▁
wandb: 
wandb: Run summary:
wandb:                  eval/f1_score 0.6872
wandb:                  eval/label_f1 0.83254
wandb:                      eval/loss 0.22641
wandb:                   eval/runtime 339.3736
wandb:        eval/samples_per_second 2.947
wandb:          eval/steps_per_second 0.368
wandb:                       eval/wer 0.098
wandb:                    train/epoch 8.94
wandb:              train/global_step 5000
wandb:            train/learning_rate 0.0
wandb:                     train/loss 0.1961
wandb:               train/total_flos 1.9683074514013055e+20
wandb:               train/train_loss 0.21677
wandb:            train/train_runtime 50642.5955
wandb: train/train_samples_per_second 12.638
wandb:   train/train_steps_per_second 0.099
wandb: 
wandb: 🚀 View run run-2024-01-08_18-44-50 at: https://wandb.ai/qmeeus/Whisper%20PEFT%20Fine-Tuning/runs/35ireexg
wandb: ️⚡ View job at https://wandb.ai/qmeeus/Whisper%20PEFT%20Fine-Tuning/jobs/QXJ0aWZhY3RDb2xsZWN0aW9uOjEyODM1Nzc0OA==/version_details/v2
wandb: Synced 5 W&B file(s), 0 media file(s), 2 artifact file(s) and 0 other file(s)
wandb: Find logs at: ./wandb/run-20240108_184452-35ireexg/logs