wav2vec2-large-mms-1b-bemba-colab
This model is a fine-tuned version of facebook/mms-1b-all on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1663
- Wer: 0.3303
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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 15
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
2.6643 | 0.26 | 200 | 0.2147 | 0.3900 |
0.4271 | 0.52 | 400 | 0.1996 | 0.3634 |
0.4004 | 0.77 | 600 | 0.1911 | 0.3595 |
0.3789 | 1.03 | 800 | 0.1905 | 0.3544 |
0.3707 | 1.29 | 1000 | 0.1821 | 0.3461 |
0.3811 | 1.55 | 1200 | 0.1815 | 0.3586 |
0.3662 | 1.8 | 1400 | 0.1811 | 0.3433 |
0.3627 | 2.06 | 1600 | 0.1814 | 0.3443 |
0.3529 | 2.32 | 1800 | 0.1807 | 0.3375 |
0.3466 | 2.58 | 2000 | 0.1758 | 0.3299 |
0.3481 | 2.84 | 2200 | 0.1781 | 0.3408 |
0.3446 | 3.09 | 2400 | 0.1761 | 0.3316 |
0.3379 | 3.35 | 2600 | 0.1702 | 0.3305 |
0.3371 | 3.61 | 2800 | 0.1668 | 0.3258 |
0.3326 | 3.87 | 3000 | 0.1661 | 0.3212 |
0.3297 | 4.12 | 3200 | 0.1706 | 0.3358 |
0.3267 | 4.38 | 3400 | 0.1707 | 0.3322 |
0.3328 | 4.64 | 3600 | 0.1663 | 0.3303 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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Model tree for csikasote/wav2vec2-large-mms-1b-bemba-colab
Base model
facebook/mms-1b-all