---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-base-Malyalam-large
  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. -->

# wav2vec2-base-Malyalam-large

This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co./facebook/wav2vec2-base-960h) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4124
- Wer: 0.4294
- Cer: 0.0876

## 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: 6
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 5.755         | 2.1622  | 300  | 3.4394          | 1.0    | 1.0    |
| 1.5526        | 4.3243  | 600  | 0.7064          | 0.7488 | 0.1865 |
| 0.6682        | 6.4865  | 900  | 0.5412          | 0.6252 | 0.1383 |
| 0.4698        | 8.6486  | 1200 | 0.4891          | 0.5767 | 0.1271 |
| 0.3632        | 10.8108 | 1500 | 0.3958          | 0.5024 | 0.1004 |
| 0.2918        | 12.9730 | 1800 | 0.4565          | 0.5020 | 0.1055 |
| 0.2335        | 15.1351 | 2100 | 0.4298          | 0.4723 | 0.0981 |
| 0.1956        | 17.2973 | 2400 | 0.3805          | 0.4466 | 0.0888 |
| 0.1665        | 19.4595 | 2700 | 0.4039          | 0.4311 | 0.0889 |
| 0.1447        | 21.6216 | 3000 | 0.4124          | 0.4294 | 0.0876 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 1.18.3
- Tokenizers 0.19.1