File size: 2,883 Bytes
98d5772 32e3647 7307bb9 98d5772 32e3647 98d5772 7307bb9 98d5772 32e3647 98d5772 05117f0 91a1e4c 98d5772 32e3647 91a1e4c 32e3647 98d5772 7307bb9 |
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 89 90 |
---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- bleu
- wer
- chrf
model-index:
- name: Whisper Small GA-EN Speech Translation
results: []
datasets:
- ymoslem/IWSLT2023-GA-EN
- ymoslem/FLEURS-GA-EN
- ymoslem/BitesizeIrish-GA-EN
- ymoslem/SpokenWords-GA-EN-MTed
language:
- ga
- en
library_name: transformers
---
<!-- 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 Small GA-EN Speech Translation
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on an unknown dataset.
The best model (this version) is at checkpoint 1400, epoch 1.51, and it achieves the following results on the evaluation set:
- Loss: 1.3989
- Bleu: 28.53
- Chrf: 44.93
- Wer: 68.1675
## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.03
- training_steps: 1500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Bleu | Chrf | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:-----:|:-----:|:---------------:|:--------:|
| 2.2789 | 0.11 | 100 | 9.07 | 25.39 | 2.0838 | 102.2963 |
| 1.9858 | 0.22 | 200 | 12.68 | 29.42 | 1.7854 | 101.1706 |
| 1.6904 | 0.32 | 300 | 11.93 | 31.4 | 1.6522 | 148.2215 |
| 1.4934 | 0.43 | 400 | 16.44 | 35.2 | 1.5699 | 95.3174 |
| 1.371 | 0.54 | 500 | 15.89 | 34.46 | 1.5181 | 100.9455 |
| 1.1806 | 0.65 | 600 | 20.62 | 40.11 | 1.4475 | 91.8955 |
| 1.0781 | 0.76 | 700 | 18.55 | 40.22 | 1.4067 | 99.5948 |
| 0.9166 | 0.86 | 800 | 26.87 | 43.16 | 1.4104 | 71.3192 |
| 0.848 | 0.97 | 900 | 25.95 | 42.61 | 1.3556 | 75.6866 |
| 0.3712 | 1.08 | 1000 | 22.4 | 41.02 | 1.3936 | 87.2580 |
| 0.4415 | 1.19 | 1100 | 28.13 | 43.0 | 1.4157 | 68.0324 |
| 0.4166 | 1.29 | 1200 | 27.75 | 44.39 | 1.4206 | 71.1391 |
| 0.387 | 1.4 | 1300 | 28.48 | 44.44 | 1.4083 | 69.4282 |
| 0.3714 | 1.51 | 1400 | 28.53 | 44.93 | 1.3989 | 68.1675 |
| 0.3695 | 1.62 | 1500 | 26.13 | 43.65 | 1.4049 | 76.9923 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2 |