File size: 2,331 Bytes
6e7014f 261966b 6e7014f 261966b 6e7014f 261966b 6e7014f |
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 |
---
base_model: vinai/bartpho-word-base
tags:
- generated_from_trainer
model-index:
- name: bartpho-word-base-ed-multi-v2
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. -->
# bartpho-word-base-ed-multi-v2
This model is a fine-tuned version of [vinai/bartpho-word-base](https://huggingface.co/vinai/bartpho-word-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0265
- F1 Micro: 0.8088
- Recall Micro: 0.8070
- Precision Micro: 0.8106
- F1 Macro: 0.6254
- Recall Macro: 0.6672
- Precision Macro: 0.6084
## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Micro | Recall Micro | Precision Micro | F1 Macro | Recall Macro | Precision Macro |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------------:|:---------------:|:--------:|:------------:|:---------------:|
| No log | 0.9987 | 393 | 0.0251 | 0.8059 | 0.8110 | 0.8008 | 0.5082 | 0.5352 | 0.5171 |
| 0.0227 | 2.0 | 787 | 0.0252 | 0.7931 | 0.7957 | 0.7906 | 0.5909 | 0.6664 | 0.5631 |
| 0.017 | 2.9987 | 1180 | 0.0249 | 0.8006 | 0.8036 | 0.7977 | 0.6057 | 0.6286 | 0.6096 |
| 0.013 | 4.0 | 1574 | 0.0260 | 0.8040 | 0.7996 | 0.8085 | 0.6024 | 0.6257 | 0.6028 |
| 0.013 | 4.9936 | 1965 | 0.0265 | 0.8088 | 0.8070 | 0.8106 | 0.6254 | 0.6672 | 0.6084 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|