transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer ga en dataset:ymoslem/IWSLT2023-GA-EN dataset:ymoslem/FLEURS-GA-EN dataset:ymoslem/BitesizeIrish-GA-EN dataset:ymoslem/SpokenWords-GA-EN-MTed base_model:openai/whisper-small base_model:finetune:openai/whisper-small license:apache-2.0 endpoints_compatible region:us
---
base_model: openai/whisper-small
datasets:
- ymoslem/IWSLT2023-GA-EN
- ymoslem/FLEURS-GA-EN
- ymoslem/BitesizeIrish-GA-EN
- ymoslem/SpokenWords-GA-EN-MTed
language:
- ga
- en
library_name: transformers
license: apache-2.0
metrics:
- bleu
- wer
- chrf
tags:
- generated_from_trainer
model-index:
- name: Whisper Small GA-EN Speech Translation
  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 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