File size: 3,090 Bytes
1662b97 52317b4 1662b97 52317b4 1662b97 52317b4 1662b97 52317b4 1662b97 |
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-medium.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ./openai/whisper-medium.en-cit-do015-wd0-lr1e-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-medium.en-cit-do015-wd0-lr1e-06-1000
This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on the SF 1000 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6953
- Wer Ortho: 26.2768
- Wer: 14.7572
## 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-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 | 1.5811 | 45.2632 | 31.9044 |
| 1.7463 | 0.8889 | 50 | 1.3848 | 39.1033 | 27.0106 |
| 1.7463 | 1.3333 | 75 | 1.2178 | 35.7505 | 23.0273 |
| 1.3387 | 1.7778 | 100 | 1.0166 | 36.1014 | 23.4446 |
| 1.3387 | 2.2222 | 125 | 0.8784 | 31.9298 | 19.1958 |
| 0.988 | 2.6667 | 150 | 0.8340 | 30.8382 | 18.4750 |
| 0.988 | 3.1111 | 175 | 0.8027 | 30.3314 | 17.7162 |
| 0.8856 | 3.5556 | 200 | 0.7812 | 29.6686 | 17.4127 |
| 0.8856 | 4.0 | 225 | 0.7651 | 30.1365 | 17.6783 |
| 0.7927 | 4.4444 | 250 | 0.7515 | 29.2008 | 16.8816 |
| 0.7927 | 4.8889 | 275 | 0.7402 | 28.2651 | 15.6677 |
| 0.7482 | 5.3333 | 300 | 0.7300 | 27.9922 | 15.5159 |
| 0.7482 | 5.7778 | 325 | 0.7217 | 27.8752 | 15.6677 |
| 0.7275 | 6.2222 | 350 | 0.7153 | 27.4854 | 15.4021 |
| 0.7275 | 6.6667 | 375 | 0.7085 | 27.3684 | 15.3642 |
| 0.7003 | 7.1111 | 400 | 0.7041 | 26.6277 | 14.6813 |
| 0.7003 | 7.5556 | 425 | 0.7002 | 26.3158 | 14.7572 |
| 0.6763 | 8.0 | 450 | 0.6973 | 26.2378 | 14.6055 |
| 0.6763 | 8.4444 | 475 | 0.6963 | 26.4327 | 14.7951 |
| 0.6687 | 8.8889 | 500 | 0.6953 | 26.2768 | 14.7572 |
### Framework versions
- Transformers 4.42.3
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1
|