File size: 2,433 Bytes
4fa9a7f 6896966 4fa9a7f 6896966 4fa9a7f 6896966 4fa9a7f |
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 76 |
---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilBERT_gptdata_with_preprocessing_grid_search
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. -->
# distilBERT_gptdata_with_preprocessing_grid_search
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co./distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2838
- Precision: 0.9548
- Recall: 0.9549
- F1: 0.9545
- Accuracy: 0.9544
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 225 | 0.2093 | 0.9466 | 0.9460 | 0.9448 | 0.945 |
| No log | 2.0 | 450 | 0.1837 | 0.9581 | 0.9578 | 0.9575 | 0.9572 |
| 0.289 | 3.0 | 675 | 0.2127 | 0.9540 | 0.9533 | 0.9527 | 0.9528 |
| 0.289 | 4.0 | 900 | 0.2200 | 0.9558 | 0.9560 | 0.9556 | 0.9556 |
| 0.0448 | 5.0 | 1125 | 0.2501 | 0.9565 | 0.9568 | 0.9562 | 0.9561 |
| 0.0448 | 6.0 | 1350 | 0.2577 | 0.9561 | 0.9559 | 0.9557 | 0.9556 |
| 0.0118 | 7.0 | 1575 | 0.2600 | 0.9559 | 0.9552 | 0.9554 | 0.955 |
| 0.0118 | 8.0 | 1800 | 0.2770 | 0.9555 | 0.9552 | 0.9552 | 0.955 |
| 0.0044 | 9.0 | 2025 | 0.2838 | 0.9548 | 0.9549 | 0.9545 | 0.9544 |
| 0.0044 | 10.0 | 2250 | 0.2838 | 0.9548 | 0.9549 | 0.9545 | 0.9544 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
|