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wav2vec2-large-mms-1b-kazakh-speech2ner-kscsyn-8b-4ep
This model is a fine-tuned version of facebook/mms-1b-all on the None dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Wer: 1.0
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 6.6358 | 0.07 | 2000 | 6.5080 | 1.0000 |
| 6.6338 | 0.15 | 4000 | 6.5080 | 1.0000 |
| 0.0 | 0.22 | 6000 | nan | 1.0 |
| 0.0 | 0.3 | 8000 | nan | 1.0 |
| 0.0 | 0.37 | 10000 | nan | 1.0 |
| 0.0 | 0.44 | 12000 | nan | 1.0 |
| 0.0 | 0.52 | 14000 | nan | 1.0 |
| 0.0 | 0.59 | 16000 | nan | 1.0 |
| 0.0 | 0.66 | 18000 | nan | 1.0 |
| 0.0 | 0.74 | 20000 | nan | 1.0 |
| 0.0 | 0.81 | 22000 | nan | 1.0 |
| 0.0 | 0.89 | 24000 | nan | 1.0 |
| 0.0 | 0.96 | 26000 | nan | 1.0 |
| 0.0 | 1.03 | 28000 | nan | 1.0 |
| 0.0 | 1.11 | 30000 | nan | 1.0 |
| 0.0 | 1.18 | 32000 | nan | 1.0 |
| 0.0 | 1.25 | 34000 | nan | 1.0 |
| 0.0 | 1.33 | 36000 | nan | 1.0 |
| 0.0 | 1.4 | 38000 | nan | 1.0 |
| 0.0 | 1.48 | 40000 | nan | 1.0 |
| 0.0 | 1.55 | 42000 | nan | 1.0 |
| 0.0 | 1.62 | 44000 | nan | 1.0 |
| 0.0 | 1.7 | 46000 | nan | 1.0 |
| 0.0 | 1.77 | 48000 | nan | 1.0 |
| 0.0 | 1.84 | 50000 | nan | 1.0 |
| 0.0 | 1.92 | 52000 | nan | 1.0 |
| 0.0 | 1.99 | 54000 | nan | 1.0 |
| 0.0 | 2.07 | 56000 | nan | 1.0 |
| 0.0 | 2.14 | 58000 | nan | 1.0 |
| 0.0 | 2.21 | 60000 | nan | 1.0 |
| 0.0 | 2.29 | 62000 | nan | 1.0 |
| 0.0 | 2.36 | 64000 | nan | 1.0 |
| 0.0 | 2.43 | 66000 | nan | 1.0 |
| 0.0 | 2.51 | 68000 | nan | 1.0 |
| 0.0 | 2.58 | 70000 | nan | 1.0 |
| 0.0 | 2.66 | 72000 | nan | 1.0 |
| 0.0 | 2.73 | 74000 | nan | 1.0 |
| 0.0 | 2.8 | 76000 | nan | 1.0 |
| 0.0 | 2.88 | 78000 | nan | 1.0 |
| 0.0 | 2.95 | 80000 | nan | 1.0 |
| 0.0 | 3.02 | 82000 | nan | 1.0 |
| 0.0 | 3.1 | 84000 | nan | 1.0 |
| 0.0 | 3.17 | 86000 | nan | 1.0 |
| 0.0 | 3.25 | 88000 | nan | 1.0 |
| 0.0 | 3.32 | 90000 | nan | 1.0 |
| 0.0 | 3.39 | 92000 | nan | 1.0 |
| 0.0 | 3.47 | 94000 | nan | 1.0 |
| 0.0 | 3.54 | 96000 | nan | 1.0 |
| 0.0 | 3.61 | 98000 | nan | 1.0 |
| 0.0 | 3.69 | 100000 | nan | 1.0 |
| 0.0 | 3.76 | 102000 | nan | 1.0 |
| 0.0 | 3.84 | 104000 | nan | 1.0 |
| 0.0 | 3.91 | 106000 | nan | 1.0 |
| 0.0 | 3.98 | 108000 | nan | 1.0 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
