honzapucalek's picture
End of training
a77a42c verified
|
raw
history blame
No virus
2.21 kB
---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- honzapucalek/impaired_v3_independent_severe
metrics:
- wer
model-index:
- name: impaired-v3-independent-severe
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: honzapucalek/impaired_v3_independent_severe cs
type: honzapucalek/impaired_v3_independent_severe
config: cs
split: test
args: cs
metrics:
- name: Wer
type: wer
value: 0.42105263157894735
---
<!-- 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. -->
# impaired-v3-independent-severe
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the honzapucalek/impaired_v3_independent_severe cs dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5988
- Wer: 0.4211
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.0001 | 95.24 | 1000 | 1.3804 | 0.4160 |
| 0.0 | 190.48 | 2000 | 1.4914 | 0.4160 |
| 0.0 | 285.71 | 3000 | 1.5487 | 0.4221 |
| 0.0 | 380.95 | 4000 | 1.5853 | 0.4251 |
| 0.0 | 476.19 | 5000 | 1.5988 | 0.4211 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1