---
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-53-ft-btb-ccv-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-btb-ccv-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: 1.6889
- Wer: 0.9480

## 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: 16
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 600
- training_steps: 6000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log        | 0.0672 | 200  | 3.0784          | 1.0    |
| No log        | 0.1344 | 400  | 2.9962          | 1.0    |
| 4.6966        | 0.2016 | 600  | 3.0380          | 1.0    |
| 4.6966        | 0.2688 | 800  | 2.9616          | 1.0    |
| 3.0067        | 0.3360 | 1000 | 2.9147          | 1.0    |
| 3.0067        | 0.4032 | 1200 | 2.9158          | 1.0    |
| 3.0067        | 0.4704 | 1400 | 2.9126          | 1.0    |
| 2.9095        | 0.5376 | 1600 | 2.8195          | 1.0    |
| 2.9095        | 0.6048 | 1800 | 2.3190          | 0.9804 |
| 2.3631        | 0.6720 | 2000 | 1.5925          | 0.9349 |
| 2.3631        | 0.7392 | 2200 | 1.3529          | 0.8784 |
| 2.3631        | 0.8065 | 2400 | 1.2185          | 0.8690 |
| 1.3164        | 0.8737 | 2600 | 1.1746          | 0.8566 |
| 1.3164        | 0.9409 | 2800 | 1.2047          | 0.8444 |
| 1.2708        | 1.0081 | 3000 | 1.3975          | 0.8781 |
| 1.2708        | 1.0753 | 3200 | 1.5273          | 0.9086 |
| 1.2708        | 1.1425 | 3400 | 1.5937          | 0.9166 |
| 1.5876        | 1.2097 | 3600 | 1.4998          | 0.9331 |
| 1.5876        | 1.2769 | 3800 | 1.6366          | 0.9646 |
| 1.6623        | 1.3441 | 4000 | 1.6667          | 0.9701 |
| 1.6623        | 1.4113 | 4200 | 1.5727          | 0.9483 |
| 1.6623        | 1.4785 | 4400 | 1.6119          | 0.9611 |
| 1.6759        | 1.5457 | 4600 | 1.5941          | 0.9337 |
| 1.6759        | 1.6129 | 4800 | 1.4534          | 0.9059 |
| 1.5779        | 1.6801 | 5000 | 2.0221          | 0.9572 |
| 1.5779        | 1.7473 | 5200 | 1.7697          | 0.9399 |
| 1.5779        | 1.8145 | 5400 | 1.6657          | 0.9377 |
| 1.775         | 1.8817 | 5600 | 1.7365          | 0.9714 |
| 1.775         | 1.9489 | 5800 | 1.6953          | 0.9580 |
| 1.7507        | 2.0161 | 6000 | 1.6889          | 0.9480 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1