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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-Yspeed |
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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-Yspeed |
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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: 0.9193 |
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- Cer: 22.7561 |
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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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| 14.1833 | 0.2580 | 200 | 4.5491 | 97.4389 | |
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| 2.5916 | 0.5160 | 400 | 2.0400 | 48.7077 | |
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| 1.351 | 0.7741 | 600 | 1.9023 | 46.5695 | |
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| 1.0665 | 1.0321 | 800 | 1.2533 | 34.7039 | |
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| 0.8141 | 1.2901 | 1000 | 1.3127 | 32.2016 | |
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| 0.7672 | 1.5481 | 1200 | 1.3379 | 33.9814 | |
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| 0.6847 | 1.8062 | 1400 | 1.2278 | 32.0489 | |
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| 0.5985 | 2.0642 | 1600 | 1.1310 | 28.4657 | |
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| 0.5208 | 2.3222 | 1800 | 1.2212 | 29.4995 | |
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| 0.4664 | 2.5802 | 2000 | 1.0708 | 26.2512 | |
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| 0.4379 | 2.8383 | 2200 | 1.0705 | 26.3804 | |
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| 0.4332 | 3.0963 | 2400 | 1.0949 | 27.4260 | |
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| 0.3778 | 3.3543 | 2600 | 0.9809 | 25.3936 | |
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| 0.3273 | 3.6123 | 2800 | 1.0045 | 24.5418 | |
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| 0.3117 | 3.8703 | 3000 | 0.9171 | 23.0146 | |
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| 0.2586 | 4.1284 | 3200 | 0.9051 | 22.5329 | |
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| 0.2273 | 4.3864 | 3400 | 0.8966 | 22.3508 | |
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| 0.2169 | 4.6444 | 3600 | 0.9430 | 23.2202 | |
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| 0.2159 | 4.9024 | 3800 | 0.9193 | 22.7561 | |
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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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