End of training

README.md

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+---
+license: apache-2.0
+base_model: rinna/japanese-wav2vec2-base
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: wav2vec2-kanji-base-unigram
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/tokudai-nishimura-lab/Emoto-ASR-training-log/runs/icxw1p2j)
+# wav2vec2-kanji-base-unigram
+
+This model is a fine-tuned version of [rinna/japanese-wav2vec2-base](https://huggingface.co/rinna/japanese-wav2vec2-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.6841
+- Cer: 0.4426
+- Wer: 1.0
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 4
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 77380
+- num_epochs: 20
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step   | Validation Loss | Cer    | Wer   |
+|:-------------:|:-----:|:------:|:---------------:|:------:|:-----:|
+| 5.0463        | 1.0   | 19348  | 7.1017          | 0.9448 | 0.999 |
+| 2.3465        | 2.0   | 38696  | 4.1177          | 0.6757 | 1.0   |
+| 1.6622        | 3.0   | 58044  | 4.1171          | 0.6136 | 1.0   |
+| 1.478         | 4.0   | 77392  | 2.8624          | 0.5836 | 1.0   |
+| 1.3639        | 5.0   | 96740  | 3.2231          | 0.5709 | 1.0   |
+| 1.2924        | 6.0   | 116088 | 3.6346          | 0.5807 | 1.0   |
+| 1.2191        | 7.0   | 135436 | 2.4840          | 0.5444 | 1.0   |
+| 1.1705        | 8.0   | 154784 | 2.5931          | 0.5403 | 1.0   |
+| 1.117         | 9.0   | 174132 | 2.4750          | 0.5263 | 1.0   |
+| 1.0689        | 10.0  | 193480 | 2.1332          | 0.5131 | 1.0   |
+| 1.0371        | 11.0  | 212828 | 2.0070          | 0.4903 | 1.0   |
+| 0.9922        | 12.0  | 232176 | 2.0196          | 0.4847 | 1.0   |
+| 0.948         | 13.0  | 251524 | 1.7148          | 0.4597 | 1.0   |
+| 0.9143        | 14.0  | 270872 | 1.5651          | 0.4506 | 1.0   |
+| 0.8841        | 15.0  | 290220 | 1.7433          | 0.4530 | 1.0   |
+| 0.8593        | 16.0  | 309568 | 1.7191          | 0.4528 | 1.0   |
+| 0.8388        | 17.0  | 328916 | 1.6598          | 0.4455 | 1.0   |
+| 0.8304        | 18.0  | 348264 | 1.6671          | 0.4434 | 1.0   |
+| 0.8219        | 19.0  | 367612 | 1.6866          | 0.4426 | 1.0   |
+| 0.8184        | 20.0  | 386960 | 1.6841          | 0.4426 | 1.0   |
+
+
+### Framework versions
+
+- Transformers 4.42.0
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

config.json

@@ -0,0 +1,107 @@
+{
+  "_name_or_path": "rinna/japanese-wav2vec2-base",
+  "activation_dropout": 0.1,
+  "adapter_attn_dim": null,
+  "adapter_kernel_size": 3,
+  "adapter_stride": 2,
+  "add_adapter": false,
+  "apply_spec_augment": true,
+  "architectures": [
+    "Wav2Vec2ForCTC"
+  ],
+  "attention_dropout": 0.1,
+  "bos_token_id": 1,
+  "classifier_proj_size": 256,
+  "codevector_dim": 256,
+  "contrastive_logits_temperature": 0.1,
+  "conv_bias": false,
+  "conv_dim": [
+    512,
+    512,
+    512,
+    512,
+    512,
+    512,
+    512
+  ],
+  "conv_kernel": [
+    10,
+    3,
+    3,
+    3,
+    3,
+    2,
+    2
+  ],
+  "conv_stride": [
+    5,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2
+  ],
+  "ctc_loss_reduction": "mean",
+  "ctc_zero_infinity": false,
+  "diversity_loss_weight": 0.1,
+  "do_stable_layer_norm": false,
+  "eos_token_id": 2,
+  "feat_extract_activation": "gelu",
+  "feat_extract_norm": "group",
+  "feat_proj_dropout": 0.0,
+  "feat_quantizer_dropout": 0.0,
+  "final_dropout": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "layerdrop": 0.1,
+  "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,
+  "model_type": "wav2vec2",
+  "num_adapter_layers": 3,
+  "num_attention_heads": 12,
+  "num_codevector_groups": 2,
+  "num_codevectors_per_group": 320,
+  "num_conv_pos_embedding_groups": 16,
+  "num_conv_pos_embeddings": 128,
+  "num_feat_extract_layers": 7,
+  "num_hidden_layers": 12,
+  "num_negatives": 100,
+  "output_hidden_size": 768,
+  "pad_token_id": 3200,
+  "proj_codevector_dim": 256,
+  "tdnn_dilation": [
+    1,
+    2,
+    3,
+    1,
+    1
+  ],
+  "tdnn_dim": [
+    512,
+    512,
+    512,
+    512,
+    1500
+  ],
+  "tdnn_kernel": [
+    5,
+    3,
+    3,
+    1,
+    1
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.42.0",
+  "use_weighted_layer_sum": false,
+  "vocab_size": 3205,
+  "xvector_output_dim": 512
+}

model.safetensors

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+size 387371316

preprocessor_config.json

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+{
+  "do_normalize": false,
+  "feature_extractor_type": "Wav2Vec2FeatureExtractor",
+  "feature_size": 1,
+  "padding_side": "right",
+  "padding_value": 0.0,
+  "return_attention_mask": false,
+  "sampling_rate": 16000
+}

training_args.bin

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