---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: TrimLesson3
  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. -->

# TrimLesson3

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0961
- Accuracy: 0.7003
- F1-score: 0.6957
- Recall-score: 0.7003
- Precision-score: 0.7014

## 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: 5e-05
- train_batch_size: 20
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1-score | Recall-score | Precision-score |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:------------:|:---------------:|
| 4.0066        | 1.0   | 2068  | 3.5593          | 0.1583   | 0.0819   | 0.1583       | 0.0794          |
| 2.5652        | 2.0   | 4136  | 2.2228          | 0.4437   | 0.3810   | 0.4437       | 0.4189          |
| 1.9375        | 3.0   | 6204  | 1.5382          | 0.5597   | 0.5157   | 0.5597       | 0.5544          |
| 2.1447        | 4.0   | 8272  | 1.3384          | 0.6030   | 0.5647   | 0.6030       | 0.5980          |
| 2.1308        | 5.0   | 10340 | 1.2420          | 0.6216   | 0.5906   | 0.6216       | 0.6206          |
| 1.7815        | 6.0   | 12408 | 1.1685          | 0.6384   | 0.6109   | 0.6384       | 0.6326          |
| 1.1674        | 7.0   | 14476 | 1.1605          | 0.6431   | 0.6197   | 0.6431       | 0.6433          |
| 1.5469        | 8.0   | 16544 | 1.1038          | 0.6674   | 0.6420   | 0.6674       | 0.6617          |
| 0.6686        | 9.0   | 18612 | 1.0640          | 0.6708   | 0.6494   | 0.6708       | 0.6588          |
| 1.2668        | 10.0  | 20680 | 1.1181          | 0.6669   | 0.6457   | 0.6669       | 0.6564          |
| 0.5084        | 11.0  | 22748 | 1.0662          | 0.6773   | 0.6597   | 0.6773       | 0.6770          |
| 1.7345        | 12.0  | 24816 | 1.0945          | 0.6783   | 0.6641   | 0.6783       | 0.6821          |
| 0.7144        | 13.0  | 26884 | 1.0492          | 0.6857   | 0.6715   | 0.6857       | 0.6903          |
| 0.712         | 14.0  | 28952 | 1.0526          | 0.6900   | 0.6791   | 0.6900       | 0.6940          |
| 2.2976        | 15.0  | 31020 | 1.0654          | 0.6960   | 0.6847   | 0.6960       | 0.7023          |
| 0.6391        | 16.0  | 33088 | 1.0770          | 0.6912   | 0.6817   | 0.6912       | 0.6929          |
| 0.9704        | 17.0  | 35156 | 1.0885          | 0.6949   | 0.6895   | 0.6949       | 0.7022          |
| 0.9055        | 18.0  | 37224 | 1.0743          | 0.6965   | 0.6916   | 0.6965       | 0.6987          |
| 2.0981        | 19.0  | 39292 | 1.0877          | 0.7025   | 0.6977   | 0.7025       | 0.7051          |
| 0.3026        | 20.0  | 41360 | 1.0961          | 0.7003   | 0.6957   | 0.7003       | 0.7014          |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu118
- Datasets 2.20.0
- Tokenizers 0.20.0