---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- ./sample_speech.py
- generated_from_trainer
model-index:
- name: en-xlsr
  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. -->

# en-xlsr

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the ./SAMPLE_SPEECH.PY - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3889
- Cer: 0.1082

## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1500
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.4503        | 1.22  | 2000  | 1.0610          | 0.2687 |
| 1.0239        | 2.45  | 4000  | 0.6962          | 0.1904 |
| 0.8977        | 3.67  | 6000  | 0.5945          | 0.1687 |
| 0.804         | 4.9   | 8000  | 0.5328          | 0.1492 |
| 0.698         | 6.12  | 10000 | 0.5014          | 0.1365 |
| 0.6426        | 7.35  | 12000 | 0.4715          | 0.1322 |
| 0.61          | 8.57  | 14000 | 0.4530          | 0.1258 |
| 0.5709        | 9.79  | 16000 | 0.4300          | 0.1201 |
| 0.5235        | 11.02 | 18000 | 0.4168          | 0.1166 |
| 0.4778        | 12.24 | 20000 | 0.4057          | 0.1129 |
| 0.4571        | 13.47 | 22000 | 0.3945          | 0.1100 |
| 0.4388        | 14.69 | 24000 | 0.3891          | 0.1081 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1