File size: 2,173 Bytes
9f27d33 f529912 9f27d33 f529912 9f27d33 f529912 9f27d33 f529912 9f27d33 f529912 9f27d33 |
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 71 72 73 74 75 76 |
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v2-atcosim
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-v2-atcosim
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0552
- Wer: 9.9694
## 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
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- training_steps: 12500
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.0038 | 8.33 | 1000 | 0.0357 | 2.7829 |
| 0.001 | 16.67 | 2000 | 0.0384 | 2.0004 |
| 0.0015 | 25.0 | 3000 | 0.0373 | 31.7142 |
| 0.0001 | 33.33 | 4000 | 0.0437 | 2.3152 |
| 0.0019 | 41.67 | 5000 | 0.0446 | 7.2375 |
| 0.0 | 50.0 | 6000 | 0.0462 | 2.9033 |
| 0.0 | 58.33 | 7000 | 0.0490 | 4.3295 |
| 0.0 | 66.67 | 8000 | 0.0509 | 5.8668 |
| 0.0 | 75.0 | 9000 | 0.0524 | 7.5014 |
| 0.0 | 83.33 | 10000 | 0.0536 | 8.6405 |
| 0.0 | 91.67 | 11000 | 0.0546 | 9.5018 |
| 0.0 | 100.0 | 12000 | 0.0552 | 9.9694 |
### Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
|