update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,69 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
metrics:
|
| 6 |
+
- accuracy
|
| 7 |
+
- f1
|
| 8 |
+
model-index:
|
| 9 |
+
- name: bert-nlp-project-ft-imdb-ds-google
|
| 10 |
+
results: []
|
| 11 |
+
---
|
| 12 |
+
|
| 13 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 14 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 15 |
+
|
| 16 |
+
# bert-nlp-project-ft-imdb-ds-google
|
| 17 |
+
|
| 18 |
+
This model is a fine-tuned version of [jestemleon/bert-nlp-project-imdb](https://huggingface.co/jestemleon/bert-nlp-project-imdb) on the None dataset.
|
| 19 |
+
It achieves the following results on the evaluation set:
|
| 20 |
+
- Loss: 0.3097
|
| 21 |
+
- Accuracy: 0.9124
|
| 22 |
+
- F1: 0.9197
|
| 23 |
+
|
| 24 |
+
## Model description
|
| 25 |
+
|
| 26 |
+
More information needed
|
| 27 |
+
|
| 28 |
+
## Intended uses & limitations
|
| 29 |
+
|
| 30 |
+
More information needed
|
| 31 |
+
|
| 32 |
+
## Training and evaluation data
|
| 33 |
+
|
| 34 |
+
More information needed
|
| 35 |
+
|
| 36 |
+
## Training procedure
|
| 37 |
+
|
| 38 |
+
### Training hyperparameters
|
| 39 |
+
|
| 40 |
+
The following hyperparameters were used during training:
|
| 41 |
+
- learning_rate: 2e-05
|
| 42 |
+
- train_batch_size: 16
|
| 43 |
+
- eval_batch_size: 16
|
| 44 |
+
- seed: 42
|
| 45 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 46 |
+
- lr_scheduler_type: linear
|
| 47 |
+
- num_epochs: 3
|
| 48 |
+
- mixed_precision_training: Native AMP
|
| 49 |
+
|
| 50 |
+
### Training results
|
| 51 |
+
|
| 52 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|
| 53 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
|
| 54 |
+
| 0.3517 | 0.37 | 196 | 0.2556 | 0.9105 | 0.9187 |
|
| 55 |
+
| 0.27 | 0.75 | 392 | 0.2369 | 0.9038 | 0.9105 |
|
| 56 |
+
| 0.2246 | 1.12 | 588 | 0.2630 | 0.9133 | 0.9205 |
|
| 57 |
+
| 0.1869 | 1.49 | 784 | 0.2885 | 0.9038 | 0.9071 |
|
| 58 |
+
| 0.1696 | 1.86 | 980 | 0.2811 | 0.9152 | 0.9233 |
|
| 59 |
+
| 0.1474 | 2.24 | 1176 | 0.2918 | 0.9190 | 0.9243 |
|
| 60 |
+
| 0.1187 | 2.61 | 1372 | 0.3045 | 0.9133 | 0.9212 |
|
| 61 |
+
| 0.1077 | 2.98 | 1568 | 0.3097 | 0.9124 | 0.9197 |
|
| 62 |
+
|
| 63 |
+
|
| 64 |
+
### Framework versions
|
| 65 |
+
|
| 66 |
+
- Transformers 4.25.1
|
| 67 |
+
- Pytorch 1.13.0+cu116
|
| 68 |
+
- Datasets 2.8.0
|
| 69 |
+
- Tokenizers 0.13.2
|