---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-53-Marathi-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-xlsr-53-Marathi-large

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3832
- Wer: 0.2102
- Cer: 0.0667

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 6.4763        | 1.7647  | 300  | 3.3057          | 1.0    | 1.0    |
| 1.3413        | 3.5294  | 600  | 0.6503          | 0.4479 | 0.1574 |
| 0.4712        | 5.2941  | 900  | 0.4442          | 0.3447 | 0.1126 |
| 0.2772        | 7.0588  | 1200 | 0.4034          | 0.2922 | 0.0970 |
| 0.1741        | 8.8235  | 1500 | 0.3750          | 0.2518 | 0.0814 |
| 0.1213        | 10.5882 | 1800 | 0.3936          | 0.2435 | 0.0787 |
| 0.0889        | 12.3529 | 2100 | 0.3841          | 0.2271 | 0.0736 |
| 0.0718        | 14.1176 | 2400 | 0.3675          | 0.2116 | 0.0680 |
| 0.0546        | 15.8824 | 2700 | 0.3755          | 0.2134 | 0.0676 |
| 0.047         | 17.6471 | 3000 | 0.3832          | 0.2102 | 0.0667 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 1.18.3
- Tokenizers 0.19.1