---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-base-Telugu-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-Telugu-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: 0.3811
- Wer: 0.3630
- Cer: 0.0716

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 7.205         | 1.9737  | 300  | 3.2285          | 1.0    | 1.0    |
| 1.3015        | 3.9474  | 600  | 0.7145          | 0.7256 | 0.1790 |
| 0.6733        | 5.9211  | 900  | 0.5099          | 0.6079 | 0.1339 |
| 0.5037        | 7.8947  | 1200 | 0.4510          | 0.5383 | 0.1146 |
| 0.4039        | 9.8684  | 1500 | 0.3932          | 0.4957 | 0.1011 |
| 0.3224        | 11.8421 | 1800 | 0.3733          | 0.4537 | 0.0909 |
| 0.2699        | 13.8158 | 2100 | 0.3685          | 0.4291 | 0.0840 |
| 0.2177        | 15.7895 | 2400 | 0.3664          | 0.3836 | 0.0747 |
| 0.19          | 17.7632 | 2700 | 0.3722          | 0.3821 | 0.0743 |
| 0.1596        | 19.7368 | 3000 | 0.3811          | 0.3630 | 0.0716 |


### Framework versions

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