---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-multiple-medical-2-1
  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. -->

# wav2vec2-multiple-medical-2-1

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2340

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 5.7848        | 0.56  | 1500  | 4.7981          |
| 3.4426        | 1.12  | 3000  | 3.3244          |
| 3.1079        | 1.68  | 4500  | 3.0999          |
| 3.0034        | 2.24  | 6000  | 2.9647          |
| 2.0403        | 2.8   | 7500  | 1.5829          |
| 1.2797        | 3.36  | 9000  | 0.9095          |
| 1.052         | 3.92  | 10500 | 0.6498          |
| 0.8326        | 4.48  | 12000 | 0.5418          |
| 0.7443        | 5.04  | 13500 | 0.4615          |
| 0.6949        | 5.6   | 15000 | 0.4191          |
| 0.6096        | 6.16  | 16500 | 0.3817          |
| 0.5699        | 6.72  | 18000 | 0.3545          |
| 0.5718        | 7.28  | 19500 | 0.3439          |
| 0.5159        | 7.84  | 21000 | 0.3243          |
| 0.4808        | 8.4   | 22500 | 0.3112          |
| 0.4979        | 8.96  | 24000 | 0.2975          |
| 0.4271        | 9.52  | 25500 | 0.2948          |
| 0.4364        | 10.08 | 27000 | 0.2818          |
| 0.4205        | 10.64 | 28500 | 0.2770          |
| 0.418         | 11.2  | 30000 | 0.2747          |
| 0.3915        | 11.76 | 31500 | 0.2695          |
| 0.4121        | 12.32 | 33000 | 0.2596          |
| 0.4057        | 12.88 | 34500 | 0.2627          |
| 0.363         | 13.44 | 36000 | 0.2617          |
| 0.3767        | 14.0  | 37500 | 0.2567          |
| 0.3804        | 14.56 | 39000 | 0.2512          |
| 0.3537        | 15.12 | 40500 | 0.2505          |
| 0.3195        | 15.68 | 42000 | 0.2508          |
| 0.311         | 16.24 | 43500 | 0.2523          |
| 0.3089        | 16.8  | 45000 | 0.2462          |
| 0.3121        | 17.36 | 46500 | 0.2463          |
| 0.3549        | 17.92 | 48000 | 0.2479          |
| 0.3111        | 18.48 | 49500 | 0.2422          |
| 0.3228        | 19.04 | 51000 | 0.2414          |
| 0.2936        | 19.6  | 52500 | 0.2415          |
| 0.28          | 20.16 | 54000 | 0.2411          |
| 0.3174        | 20.72 | 55500 | 0.2354          |
| 0.2735        | 21.28 | 57000 | 0.2335          |
| 0.3498        | 21.84 | 58500 | 0.2352          |
| 0.2958        | 22.4  | 60000 | 0.2341          |
| 0.3009        | 22.96 | 61500 | 0.2328          |
| 0.2869        | 23.52 | 63000 | 0.2352          |
| 0.2644        | 24.08 | 64500 | 0.2343          |
| 0.2692        | 24.64 | 66000 | 0.2346          |
| 0.3376        | 25.2  | 67500 | 0.2339          |
| 0.2522        | 25.76 | 69000 | 0.2340          |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.4.1+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3