metadata
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-2-malayalam-combo-v1
results: []
w2v-bert-2-malayalam-combo-v1
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the None dataset. It achieves the following results on the evaluation set:
- Loss: inf
- Wer: 0.1007
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: 5e-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_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.9859 | 0.2432 | 300 | inf | 0.4513 |
| 0.2903 | 0.4864 | 600 | inf | 0.4107 |
| 0.2294 | 0.7296 | 900 | inf | 0.3331 |
| 0.2075 | 0.9728 | 1200 | inf | 0.2968 |
| 0.1737 | 1.2161 | 1500 | inf | 0.2862 |
| 0.1561 | 1.4593 | 1800 | inf | 0.2603 |
| 0.1435 | 1.7025 | 2100 | inf | 0.2496 |
| 0.1388 | 1.9457 | 2400 | inf | 0.2329 |
| 0.1213 | 2.1889 | 2700 | inf | 0.2271 |
| 0.1168 | 2.4321 | 3000 | inf | 0.2202 |
| 0.1086 | 2.6753 | 3300 | inf | 0.2273 |
| 0.1131 | 2.9185 | 3600 | inf | 0.2132 |
| 0.0951 | 3.1617 | 3900 | inf | 0.2068 |
| 0.0851 | 3.4049 | 4200 | inf | 0.2075 |
| 0.0905 | 3.6482 | 4500 | inf | 0.1969 |
| 0.0811 | 3.8914 | 4800 | inf | 0.1941 |
| 0.0754 | 4.1346 | 5100 | inf | 0.1717 |
| 0.0653 | 4.3778 | 5400 | inf | 0.1704 |
| 0.0663 | 4.6210 | 5700 | inf | 0.1737 |
| 0.0635 | 4.8642 | 6000 | inf | 0.1551 |
| 0.0607 | 5.1074 | 6300 | inf | 0.1479 |
| 0.05 | 5.3506 | 6600 | inf | 0.1478 |
| 0.0519 | 5.5938 | 6900 | inf | 0.1441 |
| 0.048 | 5.8370 | 7200 | inf | 0.1410 |
| 0.0428 | 6.0803 | 7500 | inf | 0.1362 |
| 0.0344 | 6.3235 | 7800 | inf | 0.1325 |
| 0.0344 | 6.5667 | 8100 | inf | 0.1242 |
| 0.0361 | 6.8099 | 8400 | inf | 0.1247 |
| 0.031 | 7.0531 | 8700 | inf | 0.1227 |
| 0.0256 | 7.2963 | 9000 | inf | 0.1175 |
| 0.023 | 7.5395 | 9300 | inf | 0.1172 |
| 0.0223 | 7.7827 | 9600 | inf | 0.1161 |
| 0.0203 | 8.0259 | 9900 | inf | 0.1099 |
| 0.014 | 8.2692 | 10200 | inf | 0.1094 |
| 0.0158 | 8.5124 | 10500 | inf | 0.1081 |
| 0.0147 | 8.7556 | 10800 | inf | 0.1078 |
| 0.0132 | 8.9988 | 11100 | inf | 0.1049 |
| 0.008 | 9.2420 | 11400 | inf | 0.1048 |
| 0.0081 | 9.4852 | 11700 | inf | 0.1010 |
| 0.0081 | 9.7284 | 12000 | inf | 0.1010 |
| 0.0094 | 9.9716 | 12300 | inf | 0.1007 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1