M2LabOrg's picture
End of training
6001ca8 verified
---
language:
- pt
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- M2LabOrg/jwlang
metrics:
- wer
model-index:
- name: Whisper medium pt jwlang - Michel Mesquita
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: jwlang 1.0
type: M2LabOrg/jwlang
args: 'config: pt, split: test'
metrics:
- name: Wer
type: wer
value: 18.727050183598532
---
<!-- 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 medium pt jwlang - Michel Mesquita
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the jwlang 1.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6361
- Wer: 18.7271
## 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: 16
- 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0038 | 14.0845 | 1000 | 0.5291 | 20.3182 |
| 0.0001 | 28.1690 | 2000 | 0.6034 | 18.9718 |
| 0.0 | 42.2535 | 3000 | 0.6277 | 19.0942 |
| 0.0 | 56.3380 | 4000 | 0.6361 | 18.7271 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1