File size: 2,295 Bytes
095860f |
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 |
---
library_name: transformers
base_model: bowphs/evacun2025-1
tags:
- generated_from_trainer
model-index:
- name: evacun-lemmatization-vanilla-second-split
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. -->
# evacun-lemmatization-vanilla-second-split
This model is a fine-tuned version of [bowphs/evacun2025-1](https://huggingface.co/bowphs/evacun2025-1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2926
- Exact Match: 0.8811
## 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-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Exact Match |
|:-------------:|:-------:|:-----:|:---------------:|:-----------:|
| 0.0534 | 5.9999 | 27542 | 0.1986 | 0.8633 |
| 0.0399 | 6.9999 | 32132 | 0.2140 | 0.8587 |
| 0.0275 | 8.0 | 36723 | 0.2305 | 0.86 |
| 0.0204 | 8.9999 | 41313 | 0.2508 | 0.8654 |
| 0.0154 | 9.9998 | 45903 | 0.2628 | 0.8728 |
| 0.0124 | 11.0000 | 50494 | 0.2812 | 0.8745 |
| 0.0107 | 11.9999 | 55084 | 0.2865 | 0.8734 |
| 0.0088 | 12.9998 | 59674 | 0.2926 | 0.8811 |
| 0.0067 | 13.9999 | 64265 | 0.3054 | 0.8648 |
| 0.0055 | 14.9999 | 68855 | 0.3151 | 0.8668 |
| 0.0054 | 16.0 | 73446 | 0.3202 | 0.8737 |
| 0.0042 | 16.9999 | 78036 | 0.3277 | 0.8695 |
| 0.0041 | 17.9998 | 82626 | 0.3282 | 0.8737 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.20.0
|