wav2vec2-mms-1b-malayalam-colab-CV17.0
This model is a fine-tuned version of facebook/mms-1b-all on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 4.7578
- Wer: 1.0316
- Cer: 0.7469
- Bleu: {'bleu': 0.0, 'precisions': [0.0008639308855291577, 0.0, 0.0, 0.0], 'brevity_penalty': 0.7118010694449419, 'length_ratio': 0.7462927143778207, 'translation_length': 2315, 'reference_length': 3102}
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.15
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Bleu |
|---|---|---|---|---|---|---|
| 21.8941 | 3.1496 | 200 | 14.1370 | 1.0 | 1.0292 | {'bleu': 0.0, 'precisions': [0.0, 0.0, 0.0, 0.0], 'brevity_penalty': 0.08102287291060646, 'length_ratio': 0.2846550612508059, 'translation_length': 883, 'reference_length': 3102} |
| 8.5677 | 6.2992 | 400 | 6.3226 | 1.0071 | 0.8568 | {'bleu': 0.0, 'precisions': [0.0, 0.0, 0.0, 0.0], 'brevity_penalty': 0.2500351312096836, 'length_ratio': 0.4190844616376531, 'translation_length': 1300, 'reference_length': 3102} |
| 6.6037 | 9.4488 | 600 | 5.6520 | 1.0351 | 0.7789 | {'bleu': 0.0, 'precisions': [0.0, 0.0, 0.0, 0.0], 'brevity_penalty': 0.6082895680797644, 'length_ratio': 0.6679561573178594, 'translation_length': 2072, 'reference_length': 3102} |
| 6.0799 | 12.5984 | 800 | 5.2294 | 1.0574 | 0.7594 | {'bleu': 0.0, 'precisions': [0.00041631973355537054, 0.0, 0.0, 0.0], 'brevity_penalty': 0.7471989379147929, 'length_ratio': 0.7743391360412637, 'translation_length': 2402, 'reference_length': 3102} |
| 5.7804 | 15.7480 | 1000 | 5.1733 | 1.0329 | 0.7629 | {'bleu': 0.0, 'precisions': [0.0, 0.0, 0.0, 0.0], 'brevity_penalty': 0.6734028056038747, 'length_ratio': 0.7166344294003868, 'translation_length': 2223, 'reference_length': 3102} |
| 5.4453 | 18.8976 | 1200 | 4.9821 | 1.0525 | 0.7467 | {'bleu': 0.0, 'precisions': [0.0004042037186742118, 0.0, 0.0, 0.0], 'brevity_penalty': 0.7758159728382187, 'length_ratio': 0.7975499677627337, 'translation_length': 2474, 'reference_length': 3102} |
| 5.2983 | 22.0472 | 1400 | 4.8784 | 1.0297 | 0.7521 | {'bleu': 0.0, 'precisions': [0.0008806693086745927, 0.0, 0.0, 0.0], 'brevity_penalty': 0.693559602972643, 'length_ratio': 0.7321083172147002, 'translation_length': 2271, 'reference_length': 3102} |
| 5.0862 | 25.1969 | 1600 | 4.7948 | 1.0358 | 0.7446 | {'bleu': 0.0, 'precisions': [0.0008399832003359933, 0.0, 0.0, 0.0], 'brevity_penalty': 0.7387365301547462, 'length_ratio': 0.7675693101225016, 'translation_length': 2381, 'reference_length': 3102} |
| 4.9884 | 28.3465 | 1800 | 4.7578 | 1.0316 | 0.7479 | {'bleu': 0.0, 'precisions': [0.000864304235090752, 0.0, 0.0, 0.0], 'brevity_penalty': 0.711389009553914, 'length_ratio': 0.7459703417150225, 'translation_length': 2314, 'reference_length': 3102} |
| 5.0447 | 31.4961 | 2000 | 4.7578 | 1.0316 | 0.7469 | {'bleu': 0.0, 'precisions': [0.0008639308855291577, 0.0, 0.0, 0.0], 'brevity_penalty': 0.7118010694449419, 'length_ratio': 0.7462927143778207, 'translation_length': 2315, 'reference_length': 3102} |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for ndeclarke/wav2vec2-mms-1b-malayalam-colab-CV17.0
Base model
facebook/mms-1b-allEvaluation results
- Wer on common_voice_17_0test set self-reported1.032
- Bleu on common_voice_17_0test set self-reported[object Object]