---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: my_awesome_speach_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_speach_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: 0.8215
- Accuracy: 0.6154

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.8889  | 6    | 0.6905          | 0.6923   |
| 0.6936        | 1.9259  | 13   | 0.7083          | 0.3077   |
| 0.6859        | 2.9630  | 20   | 0.7061          | 0.3846   |
| 0.6859        | 4.0     | 27   | 0.7065          | 0.4615   |
| 0.6738        | 4.8889  | 33   | 0.7058          | 0.5385   |
| 0.6487        | 5.9259  | 40   | 0.7190          | 0.5385   |
| 0.6487        | 6.9630  | 47   | 0.6488          | 0.6154   |
| 0.5804        | 8.0     | 54   | 0.6696          | 0.6154   |
| 0.6227        | 8.8889  | 60   | 0.7988          | 0.3846   |
| 0.6227        | 9.9259  | 67   | 0.6253          | 0.6923   |
| 0.6318        | 10.9630 | 74   | 0.6760          | 0.6154   |
| 0.6617        | 12.0    | 81   | 0.9642          | 0.3077   |
| 0.6617        | 12.8889 | 87   | 0.7761          | 0.5385   |
| 0.6052        | 13.9259 | 94   | 0.8490          | 0.4615   |
| 0.5238        | 14.9630 | 101  | 0.7963          | 0.4615   |
| 0.5238        | 16.0    | 108  | 0.7485          | 0.5385   |
| 0.452         | 16.8889 | 114  | 0.7720          | 0.5385   |
| 0.3813        | 17.9259 | 121  | 0.7478          | 0.6154   |
| 0.3813        | 18.9630 | 128  | 0.8406          | 0.6154   |
| 0.4809        | 20.0    | 135  | 0.6624          | 0.6923   |
| 0.3698        | 20.8889 | 141  | 0.7520          | 0.6154   |
| 0.3698        | 21.9259 | 148  | 0.8275          | 0.5385   |
| 0.2959        | 22.9630 | 155  | 0.8472          | 0.5385   |
| 0.3976        | 24.0    | 162  | 1.0899          | 0.4615   |
| 0.3976        | 24.8889 | 168  | 0.8758          | 0.5385   |
| 0.3788        | 25.9259 | 175  | 0.5872          | 0.7692   |
| 0.3511        | 26.9630 | 182  | 0.7996          | 0.6154   |
| 0.3511        | 28.0    | 189  | 0.7726          | 0.6154   |
| 0.2797        | 28.8889 | 195  | 0.7310          | 0.6923   |
| 0.2445        | 29.9259 | 202  | 0.7223          | 0.6154   |
| 0.2445        | 30.9630 | 209  | 0.7139          | 0.6923   |
| 0.2299        | 32.0    | 216  | 0.7540          | 0.6923   |
| 0.2101        | 32.8889 | 222  | 0.7878          | 0.6154   |
| 0.2101        | 33.9259 | 229  | 0.7942          | 0.6154   |
| 0.2043        | 34.9630 | 236  | 0.8193          | 0.6154   |
| 0.1638        | 35.5556 | 240  | 0.8215          | 0.6154   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3