End of training

README.md

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+---
+base_model: Watarungurunnn/w2v-bert-2.0-japanese-CV16.0
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_16_0
+metrics:
+- wer
+model-index:
+- name: w2v-bert-2.0-japanese-CV16.0_aynita_1
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_16_0
+      type: common_voice_16_0
+      config: ja
+      split: validation
+      args: ja
+    metrics:
+    - name: Wer
+      type: wer
+      value: 32.61876963445312
+---
+
+<!-- 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. -->
+
+# w2v-bert-2.0-japanese-CV16.0_aynita_1
+
+This model is a fine-tuned version of [Watarungurunnn/w2v-bert-2.0-japanese-CV16.0](https://huggingface.co/Watarungurunnn/w2v-bert-2.0-japanese-CV16.0) on the common_voice_16_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.5149
+- Wer: 32.6188
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 40000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.1205        | 1.69  | 500  | 1.3602          | 36.4355 |
+| 0.2116        | 3.39  | 1000 | 1.4580          | 35.1067 |
+| 0.1054        | 5.08  | 1500 | 1.4180          | 34.6457 |
+| 0.0661        | 6.78  | 2000 | 1.4557          | 32.3889 |
+| 0.0208        | 8.47  | 2500 | 1.5149          | 32.6188 |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.2.0+cu121
+- Datasets 2.17.2.dev0
+- Tokenizers 0.15.1

added_tokens.json

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+  "<s>": 2557
+}

config.json

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+{
+  "_name_or_path": "Watarungurunnn/w2v-bert-2.0-japanese-CV16.0",
+  "activation_dropout": 0.0,
+  "adapter_act": "relu",
+  "adapter_kernel_size": 3,
+  "adapter_stride": 2,
+  "add_adapter": true,
+  "apply_spec_augment": false,
+  "architectures": [
+    "Wav2Vec2BertForCTC"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "classifier_proj_size": 768,
+  "codevector_dim": 768,
+  "conformer_conv_dropout": 0.1,
+  "contrastive_logits_temperature": 0.1,
+  "conv_depthwise_kernel_size": 31,
+  "ctc_loss_reduction": "mean",
+  "ctc_zero_infinity": false,
+  "diversity_loss_weight": 0.1,
+  "eos_token_id": 2,
+  "feat_proj_dropout": 0.0,
+  "feat_quantizer_dropout": 0.0,
+  "feature_projection_input_dim": 160,
+  "final_dropout": 0.1,
+  "hidden_act": "swish",
+  "hidden_dropout": 0.0,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-05,
+  "layerdrop": 0.0,
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+  "mask_feature_length": 10,
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+  "mask_feature_prob": 0.0,
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+  "mask_time_min_masks": 2,
+  "mask_time_prob": 0.0,
+  "max_source_positions": 5000,
+  "model_type": "wav2vec2-bert",
+  "num_adapter_layers": 1,
+  "num_attention_heads": 16,
+  "num_codevector_groups": 2,
+  "num_codevectors_per_group": 320,
+  "num_hidden_layers": 24,
+  "num_negatives": 100,
+  "output_hidden_size": 1024,
+  "pad_token_id": 2556,
+  "position_embeddings_type": "relative_key",
+  "proj_codevector_dim": 768,
+  "right_max_position_embeddings": 8,
+  "rotary_embedding_base": 10000,
+  "tdnn_dilation": [
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+    3,
+    1,
+    1
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+  "tdnn_dim": [
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+    512,
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+    1500
+  ],
+  "tdnn_kernel": [
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+    3,
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+    1,
+    1
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+  "torch_dtype": "float32",
+  "transformers_version": "4.37.2",
+  "use_intermediate_ffn_before_adapter": false,
+  "use_weighted_layer_sum": false,
+  "vocab_size": 2559,
+  "xvector_output_dim": 512
+}

model.safetensors

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preprocessor_config.json

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+  "padding_side": "right",
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+  "sampling_rate": 16000,
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+}

special_tokens_map.json

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tokenizer_config.json

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+  "tokenizer_class": "Wav2Vec2CTCTokenizer",
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