Model save
Browse files- README.md +73 -0
- config.json +2 -2
- generation_config.json +257 -0
- model.safetensors +1 -1
- runs/Sep30_12-11-18_whisper-finetune-2/events.out.tfevents.1727698304.whisper-finetune-2 +2 -2
README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: openai/whisper-large-v3
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tags:
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- generated_from_trainer
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metrics:
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- wer
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model-index:
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- name: whisper-large-v3-cit-do015-wd0-lr1e-06-FULL4
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# whisper-large-v3-cit-do015-wd0-lr1e-06-FULL4
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5059
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- Wer Ortho: 28.4797
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- Wer: 21.0751
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-06
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- train_batch_size: 4
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 16
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 300
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- training_steps: 1400
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
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| 0.9206 | 0.7715 | 200 | 0.6309 | 33.9104 | 25.9900 |
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| 0.6533 | 1.5429 | 400 | 0.5581 | 30.2736 | 22.5910 |
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| 0.5875 | 2.3144 | 600 | 0.5322 | 29.5128 | 22.8648 |
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| 0.5351 | 3.0858 | 800 | 0.5176 | 29.3103 | 21.8431 |
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| 0.5126 | 3.8573 | 1000 | 0.5112 | 28.7100 | 21.3222 |
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| 0.4956 | 4.6287 | 1200 | 0.5063 | 28.6053 | 21.0751 |
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| 0.4785 | 5.4002 | 1400 | 0.5059 | 28.4797 | 21.0751 |
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### Framework versions
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- Transformers 4.45.1
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- Pytorch 1.13.1+cu117
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- Datasets 3.0.1
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- Tokenizers 0.20.0
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config.json
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"_name_or_path": "openai/whisper-large-v3",
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"activation_dropout": 0.0,
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"activation_function": "gelu",
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"apply_spec_augment":
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"architectures": [
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"WhisperForConditionalGeneration"
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],
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"decoder_layerdrop": 0.0,
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"decoder_layers": 32,
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"decoder_start_token_id": 50258,
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"dropout": 0
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"encoder_attention_heads": 20,
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"encoder_ffn_dim": 5120,
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"encoder_layerdrop": 0.0,
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"_name_or_path": "openai/whisper-large-v3",
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"activation_dropout": 0.0,
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"activation_function": "gelu",
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"apply_spec_augment": false,
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"architectures": [
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"WhisperForConditionalGeneration"
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],
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"decoder_layerdrop": 0.0,
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"decoder_layers": 32,
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"decoder_start_token_id": 50258,
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"dropout": 0,
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"encoder_attention_heads": 20,
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"encoder_ffn_dim": 5120,
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"encoder_layerdrop": 0.0,
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generation_config.json
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{
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