---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-53-ft-ccv-en-cy
  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-ft-ccv-en-cy

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2765
- Wer: 0.2115

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 800
- training_steps: 9000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.9898        | 0.25  | 500  | 1.3093          | 0.7971 |
| 1.0749        | 0.5   | 1000 | 0.5816          | 0.4617 |
| 0.4332        | 0.75  | 1500 | 0.4834          | 0.4091 |
| 0.3303        | 1.01  | 2000 | 0.4203          | 0.3419 |
| 0.276         | 1.26  | 2500 | 0.3910          | 0.3186 |
| 0.2591        | 1.51  | 3000 | 0.3901          | 0.3067 |
| 0.2501        | 1.76  | 3500 | 0.3646          | 0.2895 |
| 0.224         | 2.01  | 4000 | 0.3517          | 0.2806 |
| 0.182         | 2.26  | 4500 | 0.3348          | 0.2656 |
| 0.1777        | 2.51  | 5000 | 0.3277          | 0.2612 |
| 0.1734        | 2.77  | 5500 | 0.3323          | 0.2643 |
| 0.1629        | 3.02  | 6000 | 0.3171          | 0.2485 |
| 0.1338        | 3.27  | 6500 | 0.3103          | 0.2398 |
| 0.1292        | 3.52  | 7000 | 0.2934          | 0.2268 |
| 0.1264        | 3.77  | 7500 | 0.2923          | 0.2248 |
| 0.118         | 4.02  | 8000 | 0.2880          | 0.2193 |
| 0.0996        | 4.27  | 8500 | 0.2793          | 0.2124 |
| 0.0969        | 4.52  | 9000 | 0.2765          | 0.2115 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2