---
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-malayalam-v2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# w2v-bert-malayalam-v2

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: 0.1097
- Wer: 0.0913

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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: 500
- training_steps: 38000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer    |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 0.3486        | 0.2859 | 2000  | 0.3181          | 0.4042 |
| 0.291         | 0.5718 | 4000  | 0.2474          | 0.3020 |
| 0.2196        | 0.8577 | 6000  | 0.2151          | 0.2710 |
| 0.1915        | 1.1437 | 8000  | 0.2131          | 0.2488 |
| 0.1811        | 1.4295 | 10000 | 0.1786          | 0.2204 |
| 0.1881        | 1.7154 | 12000 | 0.1720          | 0.2061 |
| 0.1598        | 2.0014 | 14000 | 0.1768          | 0.1834 |
| 0.1429        | 2.2873 | 16000 | 0.1741          | 0.1708 |
| 0.1389        | 2.5732 | 18000 | 0.1646          | 0.1560 |
| 0.1314        | 2.8591 | 20000 | 0.1387          | 0.1490 |
| 0.0953        | 3.1451 | 22000 | 0.1457          | 0.1373 |
| 0.0915        | 3.4310 | 24000 | 0.1287          | 0.1238 |
| 0.0871        | 3.7169 | 26000 | 0.1255          | 0.1145 |
| 0.0903        | 4.0029 | 28000 | 0.1181          | 0.1069 |
| 0.0723        | 4.2887 | 30000 | 0.1226          | 0.1022 |
| 0.0599        | 4.5746 | 32000 | 0.1115          | 0.0992 |
| 0.0576        | 4.8605 | 34000 | 0.1087          | 0.0977 |
| 0.0473        | 5.1465 | 36000 | 0.1079          | 0.0928 |
| 0.0485        | 5.4324 | 38000 | 0.1097          | 0.0913 |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0