File size: 1,744 Bytes
92229b0 c4cd6b8 92229b0 c4cd6b8 92229b0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 |
---
base_model: openai/whisper-base
language:
- en
license: apache-2.0
metrics:
- wer
tags:
- hf-asr-leaderboard
- generated_from_trainer
model-index:
- name: Whisper Turbo Five 5K - Chee Li
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 Turbo Five 5K - Chee Li
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co./openai/whisper-base) on the Google Fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1982
- Wer: 8.3488
## 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: 600
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.0903 | 1.0560 | 1000 | 0.1948 | 9.9042 |
| 0.0389 | 2.1119 | 2000 | 0.1943 | 9.3442 |
| 0.0212 | 3.1679 | 3000 | 0.1958 | 9.0828 |
| 0.0075 | 4.2239 | 4000 | 0.1961 | 8.4626 |
| 0.0018 | 5.2798 | 5000 | 0.1982 | 8.3488 |
### Framework versions
- Transformers 4.43.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|