Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: rinna/japanese-hubert-base
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: Hubert-common_voice-phoneme-onlyJSUT
+  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. -->
+
+# Hubert-common_voice-phoneme-onlyJSUT
+
+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: 0.1617
+- Wer: 0.998
+- Cer: 0.1060
+
+## 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: 0.0003
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 12500
+- num_epochs: 20.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Wer   | Cer    |
+|:-------------:|:-------:|:----:|:---------------:|:-----:|:------:|
+| No log        | 0.7092  | 100  | 11.3614         | 1.054 | 0.9861 |
+| No log        | 1.4184  | 200  | 5.9358          | 1.0   | 0.9851 |
+| No log        | 2.1277  | 300  | 5.3101          | 1.0   | 0.9851 |
+| No log        | 2.8369  | 400  | 4.8953          | 1.0   | 0.9851 |
+| 6.9061        | 3.5461  | 500  | 4.4021          | 1.0   | 0.9851 |
+| 6.9061        | 4.2553  | 600  | 3.9323          | 1.0   | 0.9851 |
+| 6.9061        | 4.9645  | 700  | 3.4932          | 1.0   | 0.9851 |
+| 6.9061        | 5.6738  | 800  | 3.2092          | 1.0   | 0.9850 |
+| 6.9061        | 6.3830  | 900  | 3.0484          | 1.0   | 0.9851 |
+| 3.4303        | 7.0922  | 1000 | 2.9961          | 1.0   | 0.9850 |
+| 3.4303        | 7.8014  | 1100 | 2.8000          | 1.0   | 0.9850 |
+| 3.4303        | 8.5106  | 1200 | 1.9061          | 1.0   | 0.5949 |
+| 3.4303        | 9.2199  | 1300 | 0.8767          | 1.0   | 0.1547 |
+| 3.4303        | 9.9291  | 1400 | 0.5386          | 1.0   | 0.1268 |
+| 1.6163        | 10.6383 | 1500 | 0.3820          | 1.0   | 0.1190 |
+| 1.6163        | 11.3475 | 1600 | 0.2983          | 1.0   | 0.1138 |
+| 1.6163        | 12.0567 | 1700 | 0.2524          | 1.0   | 0.1117 |
+| 1.6163        | 12.7660 | 1800 | 0.2260          | 1.0   | 0.1104 |
+| 1.6163        | 13.4752 | 1900 | 0.2096          | 1.0   | 0.1110 |
+| 0.332         | 14.1844 | 2000 | 0.1896          | 0.998 | 0.1092 |
+| 0.332         | 14.8936 | 2100 | 0.1838          | 1.0   | 0.1095 |
+| 0.332         | 15.6028 | 2200 | 0.1766          | 1.0   | 0.1081 |
+| 0.332         | 16.3121 | 2300 | 0.1688          | 0.998 | 0.1071 |
+| 0.332         | 17.0213 | 2400 | 0.1667          | 0.998 | 0.1069 |
+| 0.2296        | 17.7305 | 2500 | 0.1643          | 1.0   | 0.1069 |
+| 0.2296        | 18.4397 | 2600 | 0.1602          | 1.0   | 0.1071 |
+| 0.2296        | 19.1489 | 2700 | 0.1654          | 1.0   | 0.1068 |
+| 0.2296        | 19.8582 | 2800 | 0.1617          | 0.998 | 0.1060 |
+
+
+### Framework versions
+
+- Transformers 4.47.0.dev0
+- Pytorch 2.5.1+cu124
+- Datasets 3.1.0
+- Tokenizers 0.20.3

model.safetensors

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