|
|
--- |
|
|
license: apache-2.0 |
|
|
base_model: bert-base-cased |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- precision |
|
|
- recall |
|
|
- f1 |
|
|
- accuracy |
|
|
model-index: |
|
|
- name: assignment2_attempt10 |
|
|
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. --> |
|
|
|
|
|
# assignment2_attempt10 |
|
|
|
|
|
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.5285 |
|
|
- Precision: 0.4333 |
|
|
- Recall: 0.1102 |
|
|
- F1: 0.1757 |
|
|
- Accuracy: 0.9417 |
|
|
|
|
|
## 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 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 100 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
|
| No log | 1.0 | 128 | 0.3044 | 0.0 | 0.0 | 0.0 | 0.9385 | |
|
|
| No log | 2.0 | 256 | 0.2727 | 0.1341 | 0.0932 | 0.11 | 0.9370 | |
|
|
| No log | 3.0 | 384 | 0.3383 | 0.2973 | 0.0932 | 0.1419 | 0.9413 | |
|
|
| 0.2087 | 4.0 | 512 | 0.3512 | 0.3171 | 0.1102 | 0.1635 | 0.9409 | |
|
|
| 0.2087 | 5.0 | 640 | 0.3298 | 0.175 | 0.1186 | 0.1414 | 0.9383 | |
|
|
| 0.2087 | 6.0 | 768 | 0.3793 | 0.2209 | 0.1610 | 0.1863 | 0.9363 | |
|
|
| 0.2087 | 7.0 | 896 | 0.5285 | 0.4333 | 0.1102 | 0.1757 | 0.9417 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.34.1 |
|
|
- Pytorch 2.1.0+cu118 |
|
|
- Datasets 2.14.6 |
|
|
- Tokenizers 0.14.1 |
|
|
|
