File size: 4,231 Bytes
25474af fe015c2 25474af 3b5e4bb 25474af cbc8d0d fe015c2 25474af fe015c2 25474af fe015c2 25474af |
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 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 |
---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert_finetune_own_data_model
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_finetune_own_data_model
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: 0.0053
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 3 | 0.8131 | 1.0 | 0.25 | 0.4 | 0.76 |
| No log | 2.0 | 6 | 0.6099 | 1.0 | 0.25 | 0.4 | 0.76 |
| No log | 3.0 | 9 | 0.4666 | 1.0 | 0.25 | 0.4 | 0.76 |
| No log | 4.0 | 12 | 0.3527 | 1.0 | 0.625 | 0.7692 | 0.88 |
| No log | 5.0 | 15 | 0.2583 | 1.0 | 0.875 | 0.9333 | 0.96 |
| No log | 6.0 | 18 | 0.1838 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 7.0 | 21 | 0.1230 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 8.0 | 24 | 0.0776 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 9.0 | 27 | 0.0543 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 10.0 | 30 | 0.0427 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 11.0 | 33 | 0.0378 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 12.0 | 36 | 0.0345 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 13.0 | 39 | 0.0323 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 14.0 | 42 | 0.0280 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 15.0 | 45 | 0.0228 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 16.0 | 48 | 0.0180 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 17.0 | 51 | 0.0141 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 18.0 | 54 | 0.0117 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 19.0 | 57 | 0.0104 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 20.0 | 60 | 0.0094 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 21.0 | 63 | 0.0086 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 22.0 | 66 | 0.0079 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 23.0 | 69 | 0.0074 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 24.0 | 72 | 0.0069 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 25.0 | 75 | 0.0063 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 26.0 | 78 | 0.0059 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 27.0 | 81 | 0.0056 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 28.0 | 84 | 0.0054 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 29.0 | 87 | 0.0053 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 30.0 | 90 | 0.0053 | 1.0 | 1.0 | 1.0 | 1.0 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|