jdrt_byclass_rinnna_hubert_asr_3

README.md

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+---
+license: apache-2.0
+base_model: rinna/japanese-hubert-base
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: jdrt_byclass_rinnna_hubert_asr_3
+  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. -->
+
+# jdrt_byclass_rinnna_hubert_asr_3
+
+This model is a fine-tuned version of [rinna/japanese-hubert-base](https://huggingface.co/rinna/japanese-hubert-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4223
+- Wer: 0.4080
+- Cer: 0.2885
+
+## 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: 7.5e-05
+- train_batch_size: 256
+- eval_batch_size: 256
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 260
+- num_epochs: 50
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
+| 11.2994       | 1.0   | 53   | 6.9048          | 0.9156 | 0.9495 |
+| 5.5642        | 2.0   | 106  | 4.4074          | 0.9156 | 0.9495 |
+| 4.1184        | 3.0   | 159  | 3.5723          | 0.9156 | 0.9495 |
+| 3.2849        | 4.0   | 212  | 2.9362          | 0.9156 | 0.9495 |
+| 2.7998        | 5.0   | 265  | 2.6897          | 0.9156 | 0.9495 |
+| 2.6983        | 6.0   | 318  | 2.6367          | 0.9156 | 0.9495 |
+| 2.4519        | 7.0   | 371  | 2.2030          | 0.9960 | 0.9112 |
+| 2.1019        | 8.0   | 424  | 1.8801          | 1.0    | 0.8929 |
+| 1.8091        | 9.0   | 477  | 1.5845          | 1.0    | 0.8639 |
+| 1.5947        | 10.0  | 530  | 1.3550          | 1.0    | 0.7570 |
+| 1.3709        | 11.0  | 583  | 1.2357          | 1.0000 | 0.7344 |
+| 1.2377        | 12.0  | 636  | 1.0982          | 1.0000 | 0.6984 |
+| 1.1595        | 13.0  | 689  | 0.9865          | 0.9997 | 0.6737 |
+| 1.0386        | 14.0  | 742  | 0.9245          | 0.9125 | 0.5754 |
+| 0.928         | 15.0  | 795  | 0.8553          | 0.8591 | 0.5117 |
+| 0.8691        | 16.0  | 848  | 0.7590          | 0.8435 | 0.4966 |
+| 0.7983        | 17.0  | 901  | 0.6782          | 0.5164 | 0.3451 |
+| 0.6839        | 18.0  | 954  | 0.5806          | 0.4843 | 0.3323 |
+| 0.5901        | 19.0  | 1007 | 0.5280          | 0.4438 | 0.3133 |
+| 0.5553        | 20.0  | 1060 | 0.5312          | 0.4434 | 0.3143 |
+| 0.5274        | 21.0  | 1113 | 0.5229          | 0.4357 | 0.2939 |
+| 0.4843        | 22.0  | 1166 | 0.4674          | 0.4215 | 0.2844 |
+| 0.477         | 23.0  | 1219 | 0.4996          | 0.4335 | 0.2984 |
+| 0.4624        | 24.0  | 1272 | 0.4762          | 0.4334 | 0.3005 |
+| 0.4485        | 25.0  | 1325 | 0.4241          | 0.4286 | 0.3003 |
+| 0.4301        | 26.0  | 1378 | 0.4485          | 0.4247 | 0.2923 |
+| 0.3953        | 27.0  | 1431 | 0.4292          | 0.4175 | 0.2944 |
+| 0.401         | 28.0  | 1484 | 0.4241          | 0.4102 | 0.2868 |
+| 0.3833        | 29.0  | 1537 | 0.4053          | 0.3995 | 0.2691 |
+| 0.4125        | 30.0  | 1590 | 0.4210          | 0.4013 | 0.2690 |
+| 0.3703        | 31.0  | 1643 | 0.4385          | 0.4070 | 0.2744 |
+| 0.3441        | 32.0  | 1696 | 0.4126          | 0.4035 | 0.2718 |
+| 0.3411        | 33.0  | 1749 | 0.4286          | 0.4125 | 0.2875 |
+| 0.3302        | 34.0  | 1802 | 0.4311          | 0.4128 | 0.2943 |
+| 0.3422        | 35.0  | 1855 | 0.4350          | 0.4084 | 0.2880 |
+| 0.3428        | 36.0  | 1908 | 0.4223          | 0.4080 | 0.2885 |
+
+
+### Framework versions
+
+- Transformers 4.34.0.dev0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "rinna/japanese-hubert-base",
+  "activation_dropout": 0.1,
+  "apply_spec_augment": true,
+  "architectures": [
+    "HubertForCTC"
+  ],
+  "attention_dropout": 0.1,
+  "bos_token_id": 1,
+  "classifier_proj_size": 256,
+  "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,
+  "do_stable_layer_norm": false,
+  "eos_token_id": 2,
+  "feat_extract_activation": "gelu",
+  "feat_extract_norm": "group",
+  "feat_proj_dropout": 0.1,
+  "feat_proj_layer_norm": true,
+  "final_dropout": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout": 0,
+  "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": "hubert",
+  "num_attention_heads": 12,
+  "num_conv_pos_embedding_groups": 16,
+  "num_conv_pos_embeddings": 128,
+  "num_feat_extract_layers": 7,
+  "num_hidden_layers": 12,
+  "pad_token_id": 28,
+  "torch_dtype": "float32",
+  "transformers_version": "4.34.0.dev0",
+  "use_weighted_layer_sum": false,
+  "vocab_size": 29
+}

preprocessor_config.json

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

pytorch_model.bin

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+size 377649057

training_args.bin

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