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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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tags: |
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- automatic-speech-recognition |
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- ./sample_speech.py |
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- generated_from_trainer |
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model-index: |
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- name: zh-xlsr |
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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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# zh-xlsr |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the ./SAMPLE_SPEECH.PY - NA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8449 |
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- Cer: 0.4954 |
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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: 0.0003 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- total_eval_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: 150 |
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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 6.0153 | 0.5 | 330 | 5.3438 | 0.9522 | |
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| 5.3776 | 1.0 | 660 | 5.1534 | 0.9409 | |
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| 5.2604 | 1.5 | 990 | 5.0832 | 0.9108 | |
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| 5.2393 | 2.01 | 1320 | 5.0655 | 0.9073 | |
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| 5.1721 | 2.51 | 1650 | 5.0464 | 0.9000 | |
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| 5.1619 | 3.01 | 1980 | 5.0244 | 0.9045 | |
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| 5.1308 | 3.51 | 2310 | 5.0216 | 0.9020 | |
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| 5.0971 | 4.01 | 2640 | 4.9341 | 0.9040 | |
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| 5.0137 | 4.51 | 2970 | 4.8795 | 0.9144 | |
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| 4.9341 | 5.02 | 3300 | 4.7250 | 0.9039 | |
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| 4.6832 | 5.52 | 3630 | 4.2140 | 0.8367 | |
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| 4.1627 | 6.02 | 3960 | 3.4010 | 0.7318 | |
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| 3.5448 | 6.52 | 4290 | 2.8830 | 0.6480 | |
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| 3.2576 | 7.02 | 4620 | 2.6253 | 0.6266 | |
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| 2.8561 | 7.52 | 4950 | 2.4300 | 0.5866 | |
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| 2.7894 | 8.02 | 5280 | 2.2998 | 0.5750 | |
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| 2.6018 | 8.53 | 5610 | 2.1878 | 0.5549 | |
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| 2.546 | 9.03 | 5940 | 2.1450 | 0.5351 | |
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| 2.3787 | 9.53 | 6270 | 2.1027 | 0.5340 | |
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| 2.335 | 10.03 | 6600 | 2.0304 | 0.5166 | |
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| 2.2138 | 10.53 | 6930 | 2.0100 | 0.5165 | |
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| 2.2381 | 11.03 | 7260 | 1.9651 | 0.5031 | |
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| 2.1108 | 11.53 | 7590 | 1.9666 | 0.5035 | |
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| 2.0916 | 12.04 | 7920 | 1.9136 | 0.4998 | |
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| 2.0229 | 12.54 | 8250 | 1.8988 | 0.5028 | |
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| 2.0056 | 13.04 | 8580 | 1.8769 | 0.4996 | |
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| 1.9245 | 13.54 | 8910 | 1.8716 | 0.4955 | |
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| 1.9378 | 14.04 | 9240 | 1.8561 | 0.4946 | |
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| 1.9003 | 14.54 | 9570 | 1.8485 | 0.4936 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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