mms-1b-nyagen-balanced-model
This model is a fine-tuned version of facebook/mms-1b-all on the NYAGEN - NYA dataset. It achieves the following results on the evaluation set:
- Loss: 0.1803
- Wer: 0.2549
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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 30.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
7.181 | 0.2762 | 100 | 0.6055 | 0.5247 |
0.5071 | 0.5525 | 200 | 0.2452 | 0.3594 |
0.3791 | 0.8287 | 300 | 0.2159 | 0.3232 |
0.3464 | 1.1050 | 400 | 0.2059 | 0.3047 |
0.3326 | 1.3812 | 500 | 0.1919 | 0.2943 |
0.322 | 1.6575 | 600 | 0.1868 | 0.2861 |
0.3025 | 1.9337 | 700 | 0.1850 | 0.2902 |
0.2939 | 2.2099 | 800 | 0.1777 | 0.2698 |
0.2971 | 2.4862 | 900 | 0.1716 | 0.2675 |
0.2787 | 2.7624 | 1000 | 0.1750 | 0.2716 |
0.32 | 3.0387 | 1100 | 0.1725 | 0.2734 |
0.2738 | 3.3149 | 1200 | 0.1803 | 0.2544 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for csikasote/mms-1b-nyagen-balanced-model
Base model
facebook/mms-1b-all