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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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base_model: facebook/w2v-bert-2.0 |
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datasets: |
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- common_voice_16_0 |
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metrics: |
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- wer |
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model-index: |
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- name: w2v-bert-2.0-bangala-gpu-CV16.0_v2 |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: common_voice_16_0 |
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type: common_voice_16_0 |
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config: bn |
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split: test |
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args: bn |
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metrics: |
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- type: wer |
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value: 0.4811011116993118 |
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name: Wer |
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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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# w2v-bert-2.0-bangala-gpu-CV16.0_v2 |
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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the common_voice_16_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4490 |
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- Wer: 0.4811 |
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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: 4.42184e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 500 |
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- num_epochs: 10 |
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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 | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 3.5221 | 0.31 | 300 | 0.5900 | 0.6271 | |
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| 1.2024 | 0.63 | 600 | 0.4088 | 0.4071 | |
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| 0.9149 | 0.94 | 900 | 0.3200 | 0.3270 | |
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| 0.8124 | 1.26 | 1200 | 0.2965 | 0.3080 | |
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| 0.7028 | 1.57 | 1500 | 0.2759 | 0.2884 | |
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| 0.6301 | 1.89 | 1800 | 0.2435 | 0.2671 | |
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| 0.6147 | 2.2 | 2100 | 0.2335 | 0.2477 | |
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| 0.6304 | 2.52 | 2400 | 0.2248 | 0.2458 | |
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| 0.5921 | 2.83 | 2700 | 0.2326 | 0.2441 | |
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| 0.495 | 3.15 | 3000 | 0.2180 | 0.2378 | |
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| 0.4987 | 3.46 | 3300 | 0.2139 | 0.2227 | |
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| 0.5669 | 3.78 | 3600 | 0.2097 | 0.2236 | |
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| 0.5904 | 4.09 | 3900 | 0.2038 | 0.2178 | |
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| 0.6016 | 4.41 | 4200 | 0.2091 | 0.2131 | |
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| 0.5325 | 4.72 | 4500 | 0.2064 | 0.2147 | |
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| 0.5271 | 5.04 | 4800 | 0.2002 | 0.2159 | |
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| 0.5229 | 5.35 | 5100 | 0.2069 | 0.2209 | |
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| 0.5843 | 5.67 | 5400 | 0.2090 | 0.2202 | |
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| 0.5477 | 5.98 | 5700 | 0.2085 | 0.2175 | |
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| 0.508 | 6.3 | 6000 | 0.2046 | 0.2158 | |
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| 0.5226 | 6.61 | 6300 | 0.2515 | 0.3250 | |
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| 0.7576 | 6.93 | 6600 | 0.2343 | 0.2364 | |
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| 1.0089 | 7.24 | 6900 | 0.2731 | 0.2713 | |
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| 0.9462 | 7.56 | 7200 | 0.2588 | 0.2648 | |
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| 0.8648 | 7.87 | 7500 | 0.2916 | 0.3393 | |
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| 1.1282 | 8.19 | 7800 | 0.3830 | 0.4583 | |
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| 1.3279 | 8.5 | 8100 | 0.3910 | 0.4117 | |
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| 1.2722 | 8.82 | 8400 | 0.4424 | 0.3442 | |
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| 1.2886 | 9.13 | 8700 | 0.4421 | 0.4011 | |
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| 1.3274 | 9.45 | 9000 | 0.4483 | 0.4769 | |
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| 1.3235 | 9.76 | 9300 | 0.4490 | 0.4811 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.0 |
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