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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-1b |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: wav2vec2-1b-Yfreq_pause |
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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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# wav2vec2-1b-Yfreq_pause |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2859 |
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- Cer: 33.4880 |
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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: 0.0001 |
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- train_batch_size: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_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: 50 |
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- num_epochs: 5 |
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- mixed_precision_training: Native AMP |
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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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| 12.7189 | 0.2580 | 200 | 4.6447 | 97.3156 | |
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| 3.4682 | 0.5160 | 400 | 2.9509 | 67.6574 | |
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| 1.7355 | 0.7741 | 600 | 2.5755 | 56.9666 | |
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| 1.3168 | 1.0321 | 800 | 1.8127 | 48.0557 | |
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| 1.0608 | 1.2901 | 1000 | 1.6916 | 45.5240 | |
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| 0.9486 | 1.5481 | 1200 | 1.5227 | 41.0009 | |
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| 0.8555 | 1.8062 | 1400 | 1.8282 | 48.3905 | |
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| 0.7964 | 2.0642 | 1600 | 2.1936 | 54.9988 | |
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| 0.6832 | 2.3222 | 1800 | 1.6408 | 40.3783 | |
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| 0.5939 | 2.5802 | 2000 | 1.4571 | 39.3327 | |
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| 0.5738 | 2.8383 | 2200 | 1.3655 | 37.2827 | |
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| 0.4881 | 3.0963 | 2400 | 1.3322 | 34.9977 | |
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| 0.4278 | 3.3543 | 2600 | 1.4489 | 36.8832 | |
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| 0.3979 | 3.6123 | 2800 | 1.4433 | 37.5940 | |
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| 0.36 | 3.8703 | 3000 | 1.3372 | 36.1490 | |
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| 0.3348 | 4.1284 | 3200 | 1.3533 | 35.6203 | |
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| 0.2949 | 4.3864 | 3400 | 1.3401 | 34.7568 | |
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| 0.2703 | 4.6444 | 3600 | 1.3240 | 34.6746 | |
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| 0.2519 | 4.9024 | 3800 | 1.2859 | 33.4880 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.3.1.post100 |
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- Datasets 2.19.1 |
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- Tokenizers 0.20.1 |
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