---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: my_awesome_asr_mind_model
  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. -->

# my_awesome_asr_mind_model

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8925
- Wer: 0.4558

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.5119        | 1.77  | 100  | 4.1083          | 1.0    |
| 3.287         | 3.54  | 200  | 3.2437          | 1.0    |
| 3.1513        | 5.31  | 300  | 3.1230          | 1.0    |
| 3.0487        | 7.08  | 400  | 3.0786          | 1.0    |
| 3.0241        | 8.85  | 500  | 3.0934          | 1.0    |
| 2.9968        | 10.62 | 600  | 2.9948          | 1.0    |
| 2.9601        | 12.39 | 700  | 2.9549          | 1.0    |
| 2.9061        | 14.16 | 800  | 2.8990          | 1.0    |
| 2.3543        | 15.93 | 900  | 2.2582          | 0.9272 |
| 1.3794        | 17.7  | 1000 | 1.7532          | 0.8179 |
| 0.8947        | 19.47 | 1100 | 1.2148          | 0.6710 |
| 0.5989        | 21.24 | 1200 | 1.3229          | 0.5579 |
| 0.5861        | 23.01 | 1300 | 1.4233          | 0.5267 |
| 0.4311        | 24.78 | 1400 | 1.5458          | 0.5104 |
| 0.3286        | 26.55 | 1500 | 1.6509          | 0.5039 |
| 0.2765        | 28.32 | 1600 | 1.6818          | 0.4948 |
| 0.2541        | 30.09 | 1700 | 1.7650          | 0.4629 |
| 0.2151        | 31.86 | 1800 | 1.7185          | 0.4460 |
| 0.1959        | 33.63 | 1900 | 1.9164          | 0.4577 |
| 0.1909        | 35.4  | 2000 | 1.8925          | 0.4558 |


### Framework versions

- Transformers 4.37.1
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1