File size: 2,116 Bytes
bec3194 |
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 |
---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v3-cit-do015-wd0-lr1e-06-FULL4
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-v3-cit-do015-wd0-lr1e-06-FULL4
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5059
- Wer Ortho: 28.4797
- Wer: 21.0751
## 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: 300
- training_steps: 1400
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.9206 | 0.7715 | 200 | 0.6309 | 33.9104 | 25.9900 |
| 0.6533 | 1.5429 | 400 | 0.5581 | 30.2736 | 22.5910 |
| 0.5875 | 2.3144 | 600 | 0.5322 | 29.5128 | 22.8648 |
| 0.5351 | 3.0858 | 800 | 0.5176 | 29.3103 | 21.8431 |
| 0.5126 | 3.8573 | 1000 | 0.5112 | 28.7100 | 21.3222 |
| 0.4956 | 4.6287 | 1200 | 0.5063 | 28.6053 | 21.0751 |
| 0.4785 | 5.4002 | 1400 | 0.5059 | 28.4797 | 21.0751 |
### Framework versions
- Transformers 4.45.1
- Pytorch 1.13.1+cu117
- Datasets 3.0.1
- Tokenizers 0.20.0
|