---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
datasets:
- ami
metrics:
- wer
model-index:
- name: 6e-5_4000eval
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: ami
      type: ami
      config: ihm
      split: None
      args: ihm
    metrics:
    - name: Wer
      type: wer
      value: 0.2470857142857143
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/jadorantes2-utep/%3Cmy-amazing-projecttokenizer6e-5eval4000%3E/runs/c41b6hhn)
# 6e-5_4000eval

This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co./facebook/wav2vec2-base-960h) on the ami dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8508
- Wer: 0.2471

## 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: 6e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss | Wer    |
|:-------------:|:--------:|:----:|:---------------:|:------:|
| No log        | 7.5758   | 250  | 5.4590          | 0.9995 |
| 9.3761        | 15.1515  | 500  | 3.7020          | 0.9995 |
| 9.3761        | 22.7273  | 750  | 3.0706          | 0.9995 |
| 3.2176        | 30.3030  | 1000 | 3.0517          | 0.9995 |
| 3.2176        | 37.8788  | 1250 | 1.8920          | 0.7721 |
| 2.0444        | 45.4545  | 1500 | 1.3641          | 0.3488 |
| 2.0444        | 53.0303  | 1750 | 1.1031          | 0.2779 |
| 0.8363        | 60.6061  | 2000 | 1.1269          | 0.2679 |
| 0.8363        | 68.1818  | 2250 | 1.0291          | 0.2656 |
| 0.6824        | 75.7576  | 2500 | 0.9712          | 0.2629 |
| 0.6824        | 83.3333  | 2750 | 0.8902          | 0.2619 |
| 0.5956        | 90.9091  | 3000 | 0.8432          | 0.2441 |
| 0.5956        | 98.4848  | 3250 | 0.8714          | 0.2485 |
| 0.4071        | 106.0606 | 3500 | 0.8222          | 0.2478 |
| 0.4071        | 113.6364 | 3750 | 0.8398          | 0.2501 |
| 0.4479        | 121.2121 | 4000 | 0.8508          | 0.2471 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1