---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# w2v-bert-2-malayalam-combo-v1

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/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