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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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datasets: |
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- common_voice |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-ia |
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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-ia |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1452 |
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- Wer: 0.1253 |
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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: 3e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 4 |
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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: 400 |
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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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| 7.432 | 1.87 | 400 | 2.9636 | 1.0 | |
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| 2.6922 | 3.74 | 800 | 2.2111 | 0.9977 | |
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| 1.2581 | 5.61 | 1200 | 0.4864 | 0.4028 | |
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| 0.6232 | 7.48 | 1600 | 0.2807 | 0.2413 | |
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| 0.4479 | 9.35 | 2000 | 0.2219 | 0.1885 | |
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| 0.3654 | 11.21 | 2400 | 0.1886 | 0.1606 | |
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| 0.323 | 13.08 | 2800 | 0.1716 | 0.1444 | |
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| 0.2935 | 14.95 | 3200 | 0.1687 | 0.1443 | |
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| 0.2707 | 16.82 | 3600 | 0.1632 | 0.1382 | |
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| 0.2559 | 18.69 | 4000 | 0.1507 | 0.1337 | |
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| 0.2433 | 20.56 | 4400 | 0.1572 | 0.1358 | |
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| 0.2338 | 22.43 | 4800 | 0.1489 | 0.1305 | |
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| 0.2258 | 24.3 | 5200 | 0.1485 | 0.1278 | |
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| 0.2218 | 26.17 | 5600 | 0.1470 | 0.1272 | |
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| 0.2169 | 28.04 | 6000 | 0.1470 | 0.1270 | |
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| 0.2117 | 29.91 | 6400 | 0.1452 | 0.1253 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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