File size: 3,085 Bytes
ab2e0df 6dfd8b0 ab2e0df 6dfd8b0 ab2e0df 6dfd8b0 ab2e0df 6dfd8b0 ab2e0df |
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 77 78 79 80 81 82 83 84 85 86 87 88 |
---
language:
- en
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ./openai/whisper-large-v3-cit-do015-wd0-lr5e-06-1000
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. -->
# ./openai/whisper-large-v3-cit-do015-wd0-lr5e-06-1000
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the SF 1000 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4753
- Wer Ortho: 23.5867
- Wer: 12.4052
## 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: 5e-06
- 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: 500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| No log | 0.4444 | 25 | 1.1494 | 33.5283 | 21.6616 |
| 1.2689 | 0.8889 | 50 | 0.6362 | 28.0702 | 14.9090 |
| 1.2689 | 1.3333 | 75 | 0.5078 | 24.3275 | 12.2534 |
| 0.5452 | 1.7778 | 100 | 0.3860 | 23.1189 | 11.7602 |
| 0.5452 | 2.2222 | 125 | 0.3789 | 23.1969 | 11.1912 |
| 0.3251 | 2.6667 | 150 | 0.3691 | 24.0546 | 11.4568 |
| 0.3251 | 3.1111 | 175 | 0.3545 | 23.9376 | 11.5706 |
| 0.2441 | 3.5556 | 200 | 0.3701 | 25.3411 | 13.2018 |
| 0.2441 | 4.0 | 225 | 0.3564 | 21.4815 | 9.9393 |
| 0.1651 | 4.4444 | 250 | 0.3909 | 22.5731 | 10.3566 |
| 0.1651 | 4.8889 | 275 | 0.3708 | 24.6394 | 13.0121 |
| 0.1394 | 5.3333 | 300 | 0.3928 | 24.7563 | 13.2018 |
| 0.1394 | 5.7778 | 325 | 0.4097 | 24.6784 | 13.2018 |
| 0.1062 | 6.2222 | 350 | 0.4270 | 25.3021 | 13.4294 |
| 0.1062 | 6.6667 | 375 | 0.4133 | 24.2105 | 12.8225 |
| 0.0831 | 7.1111 | 400 | 0.4275 | 23.9766 | 13.0880 |
| 0.0831 | 7.5556 | 425 | 0.4592 | 23.1579 | 12.3293 |
| 0.065 | 8.0 | 450 | 0.4617 | 23.9376 | 12.5190 |
| 0.065 | 8.4444 | 475 | 0.4685 | 23.5088 | 12.4810 |
| 0.0558 | 8.8889 | 500 | 0.4753 | 23.5867 | 12.4052 |
### Framework versions
- Transformers 4.42.3
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1
|