|
--- |
|
language: |
|
- en |
|
license: apache-2.0 |
|
base_model: openai/whisper-large-v3 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: ./whisper-large-cit-synth-do0.15-wd0-lr1e-05 |
|
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-cit-synth-do0.15-wd0-lr1e-05 |
|
|
|
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the SF 200 synth 2000 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3455 |
|
- Wer: 15.0359 |
|
|
|
## 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: 4 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- gradient_accumulation_steps: 4 |
|
- 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: 100 |
|
- training_steps: 300 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:------:|:----:|:---------------:|:-------:| |
|
| 0.5226 | 0.4040 | 50 | 0.3027 | 17.5235 | |
|
| 0.2202 | 0.8081 | 100 | 0.2734 | 16.6022 | |
|
| 0.1105 | 1.2121 | 150 | 0.2876 | 16.1047 | |
|
| 0.0613 | 1.6162 | 200 | 0.2642 | 14.3542 | |
|
| 0.0504 | 2.0202 | 250 | 0.3025 | 14.3910 | |
|
| 0.0158 | 2.4242 | 300 | 0.3455 | 15.0359 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 1.13.1+cu117 |
|
- Datasets 2.19.2 |
|
- Tokenizers 0.19.1 |
|
|
