File size: 1,883 Bytes
40a346c ad27b81 0be0ab0 40a346c 0be0ab0 40a346c c1f98e0 40a346c ad27b81 40a346c | 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 | ---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: starclass_bert
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. -->
# starclass_bert
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: 0.1168
- Accuracy: 0.9683
- Precision: 0.9718
- Recall: 0.9683
- F1: 0.9683
## 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: 16
- eval_batch_size: 16
- seed: 42
- 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 | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.2759 | 1.0 | 16 | 0.7935 | 0.9048 | 0.9073 | 0.9048 | 0.9043 |
| 0.5557 | 2.0 | 32 | 0.3849 | 0.9048 | 0.9133 | 0.9048 | 0.9029 |
| 0.3352 | 3.0 | 48 | 0.1927 | 0.9365 | 0.9418 | 0.9365 | 0.9372 |
| 0.1037 | 4.0 | 64 | 0.1253 | 0.9683 | 0.9718 | 0.9683 | 0.9683 |
| 0.0465 | 5.0 | 80 | 0.1168 | 0.9683 | 0.9718 | 0.9683 | 0.9683 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.15.2
|