---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-et-clinic
  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. -->

# whisper-large-et-clinic

This model is a fine-tuned version of [agnesluhtaru/whisper-large-et-ERR2020-v2](https://huggingface.co/agnesluhtaru/whisper-large-et-ERR2020-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4132
- Wer: 15.7347

## 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: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0297        | 4.03  | 500  | 0.3037          | 16.7147 |
| 0.0057        | 8.06  | 1000 | 0.3435          | 15.9496 |
| 0.0049        | 12.1  | 1500 | 0.3610          | 16.8737 |
| 0.0015        | 16.13 | 2000 | 0.3610          | 16.1258 |
| 0.001         | 20.16 | 2500 | 0.3868          | 16.0356 |
| 0.0011        | 24.19 | 3000 | 0.3949          | 15.8293 |
| 0.0006        | 28.22 | 3500 | 0.4028          | 15.7476 |
| 0.0008        | 32.26 | 4000 | 0.4132          | 15.7347 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.12.1+rocm5.1.1
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2