File size: 2,219 Bytes
75f11b7 93252d3 75f11b7 93252d3 75f11b7 93252d3 |
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 |
---
license: mit
base_model: microsoft/git-base
tags:
- generated_from_trainer
model-index:
- name: git-base-naruto
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. -->
# git-base-naruto
This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0529
- Wer Score: 1.4091
## 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-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Score |
|:-------------:|:-------:|:----:|:---------------:|:---------:|
| 7.3586 | 3.7037 | 50 | 4.5383 | 8.8030 |
| 2.3507 | 7.4074 | 100 | 0.4544 | 0.4697 |
| 0.1281 | 11.1111 | 150 | 0.0543 | 0.5152 |
| 0.0161 | 14.8148 | 200 | 0.0491 | 0.4545 |
| 0.0115 | 18.5185 | 250 | 0.0501 | 0.4394 |
| 0.0099 | 22.2222 | 300 | 0.0528 | 0.4697 |
| 0.0085 | 25.9259 | 350 | 0.0536 | 0.4697 |
| 0.0075 | 29.6296 | 400 | 0.0532 | 0.4848 |
| 0.0068 | 33.3333 | 450 | 0.0520 | 0.4697 |
| 0.0061 | 37.0370 | 500 | 0.0528 | 0.6818 |
| 0.0054 | 40.7407 | 550 | 0.0530 | 0.8030 |
| 0.0044 | 44.4444 | 600 | 0.0535 | 1.2121 |
| 0.0038 | 48.1481 | 650 | 0.0529 | 1.4091 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|