File size: 2,746 Bytes
e156bb8 |
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 |
---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-ia-checkpoint
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. -->
# bert-ia-checkpoint
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7216
- Accuracy: 0.7229
- F1 Macro: 0.6963
- Precision Macro: 0.7200
- Recall Macro: 0.6916
- Auc: 0.7626
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro | Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|:------:|
| No log | 1.0 | 79 | 0.6736 | 0.7261 | 0.7028 | 0.7210 | 0.6981 | 0.7428 |
| No log | 2.0 | 158 | 0.8024 | 0.7006 | 0.6975 | 0.6995 | 0.7070 | 0.7566 |
| No log | 3.0 | 237 | 0.9896 | 0.7389 | 0.7226 | 0.7307 | 0.7189 | 0.7613 |
| No log | 4.0 | 316 | 1.3463 | 0.7229 | 0.7032 | 0.7145 | 0.6992 | 0.7444 |
| No log | 5.0 | 395 | 1.4706 | 0.7357 | 0.7246 | 0.7256 | 0.7238 | 0.7536 |
| No log | 6.0 | 474 | 1.6432 | 0.7420 | 0.7264 | 0.7339 | 0.7228 | 0.7518 |
| 0.176 | 7.0 | 553 | 1.7216 | 0.7229 | 0.6963 | 0.7200 | 0.6916 | 0.7626 |
| 0.176 | 8.0 | 632 | 1.7837 | 0.7357 | 0.7078 | 0.7383 | 0.7023 | 0.7596 |
| 0.176 | 9.0 | 711 | 1.7627 | 0.7325 | 0.7129 | 0.7256 | 0.7085 | 0.7611 |
| 0.176 | 10.0 | 790 | 1.7560 | 0.7357 | 0.7188 | 0.7275 | 0.7149 | 0.7610 |
### Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
|