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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-telugu-asr |
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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-large-xls-r-300m-telugu-asr |
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This model is a fine-tuned version of [henilp105/wav2vec2-large-xls-r-300m-telugu-asr](https://huggingface.co/henilp105/wav2vec2-large-xls-r-300m-telugu-asr) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.0959 |
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- Wer: 1.0406 |
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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: 8 |
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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: 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: 500 |
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- num_epochs: 30 |
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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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| 3.6321 | 2.04 | 200 | 2.3063 | 0.9872 | |
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| 1.8629 | 4.08 | 400 | 2.4143 | 0.9926 | |
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| 1.3881 | 6.12 | 600 | 2.5862 | 0.9795 | |
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| 1.0565 | 8.16 | 800 | 2.6708 | 1.0191 | |
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| 0.7681 | 10.2 | 1000 | 3.1001 | 0.9992 | |
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| 0.5867 | 12.24 | 1200 | 3.4503 | 1.0228 | |
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| 0.4289 | 14.29 | 1400 | 3.5382 | 1.0165 | |
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| 0.3618 | 16.33 | 1600 | 3.5116 | 0.9835 | |
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| 0.3229 | 18.37 | 1800 | 3.6524 | 1.0093 | |
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| 0.2483 | 20.41 | 2000 | 3.6222 | 1.0319 | |
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| 0.2215 | 22.45 | 2200 | 3.9824 | 1.0414 | |
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| 0.1833 | 24.49 | 2400 | 3.9272 | 1.0393 | |
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| 0.1706 | 26.53 | 2600 | 3.9290 | 1.0425 | |
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| 0.1463 | 28.57 | 2800 | 4.0959 | 1.0406 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.10.0+cu113 |
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- Datasets 1.18.3 |
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- Tokenizers 0.13.2 |
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