update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,75 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
metrics:
|
| 6 |
+
- accuracy
|
| 7 |
+
model-index:
|
| 8 |
+
- name: distilbert-base-uncased__hate_speech_offensive__train-32-5
|
| 9 |
+
results: []
|
| 10 |
+
---
|
| 11 |
+
|
| 12 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 13 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 14 |
+
|
| 15 |
+
# distilbert-base-uncased__hate_speech_offensive__train-32-5
|
| 16 |
+
|
| 17 |
+
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
|
| 18 |
+
It achieves the following results on the evaluation set:
|
| 19 |
+
- Loss: 1.1327
|
| 20 |
+
- Accuracy: 0.57
|
| 21 |
+
|
| 22 |
+
## Model description
|
| 23 |
+
|
| 24 |
+
More information needed
|
| 25 |
+
|
| 26 |
+
## Intended uses & limitations
|
| 27 |
+
|
| 28 |
+
More information needed
|
| 29 |
+
|
| 30 |
+
## Training and evaluation data
|
| 31 |
+
|
| 32 |
+
More information needed
|
| 33 |
+
|
| 34 |
+
## Training procedure
|
| 35 |
+
|
| 36 |
+
### Training hyperparameters
|
| 37 |
+
|
| 38 |
+
The following hyperparameters were used during training:
|
| 39 |
+
- learning_rate: 2e-05
|
| 40 |
+
- train_batch_size: 4
|
| 41 |
+
- eval_batch_size: 4
|
| 42 |
+
- seed: 42
|
| 43 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 44 |
+
- lr_scheduler_type: linear
|
| 45 |
+
- num_epochs: 50
|
| 46 |
+
- mixed_precision_training: Native AMP
|
| 47 |
+
|
| 48 |
+
### Training results
|
| 49 |
+
|
| 50 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| 51 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
| 52 |
+
| 1.0972 | 1.0 | 19 | 1.0470 | 0.45 |
|
| 53 |
+
| 0.9738 | 2.0 | 38 | 0.9244 | 0.65 |
|
| 54 |
+
| 0.7722 | 3.0 | 57 | 0.8612 | 0.65 |
|
| 55 |
+
| 0.4929 | 4.0 | 76 | 0.6759 | 0.75 |
|
| 56 |
+
| 0.2435 | 5.0 | 95 | 0.7273 | 0.7 |
|
| 57 |
+
| 0.0929 | 6.0 | 114 | 0.6444 | 0.85 |
|
| 58 |
+
| 0.0357 | 7.0 | 133 | 0.7671 | 0.8 |
|
| 59 |
+
| 0.0173 | 8.0 | 152 | 0.7599 | 0.75 |
|
| 60 |
+
| 0.0121 | 9.0 | 171 | 0.8140 | 0.8 |
|
| 61 |
+
| 0.0081 | 10.0 | 190 | 0.7861 | 0.8 |
|
| 62 |
+
| 0.0066 | 11.0 | 209 | 0.8318 | 0.8 |
|
| 63 |
+
| 0.0057 | 12.0 | 228 | 0.8777 | 0.8 |
|
| 64 |
+
| 0.0053 | 13.0 | 247 | 0.8501 | 0.8 |
|
| 65 |
+
| 0.004 | 14.0 | 266 | 0.8603 | 0.8 |
|
| 66 |
+
| 0.004 | 15.0 | 285 | 0.8787 | 0.8 |
|
| 67 |
+
| 0.0034 | 16.0 | 304 | 0.8969 | 0.8 |
|
| 68 |
+
|
| 69 |
+
|
| 70 |
+
### Framework versions
|
| 71 |
+
|
| 72 |
+
- Transformers 4.15.0
|
| 73 |
+
- Pytorch 1.10.2+cu102
|
| 74 |
+
- Datasets 1.18.2
|
| 75 |
+
- Tokenizers 0.10.3
|