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 |
+
model-index:
|
| 8 |
+
- name: BERT_MC_OpenBookQA_w_wrong_context
|
| 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 |
+
# BERT_MC_OpenBookQA_w_wrong_context
|
| 16 |
+
|
| 17 |
+
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
|
| 18 |
+
It achieves the following results on the evaluation set:
|
| 19 |
+
- Loss: 0.7450
|
| 20 |
+
- Accuracy: 0.922
|
| 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: 5e-05
|
| 40 |
+
- train_batch_size: 16
|
| 41 |
+
- eval_batch_size: 16
|
| 42 |
+
- seed: 42
|
| 43 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 44 |
+
- lr_scheduler_type: linear
|
| 45 |
+
- num_epochs: 11
|
| 46 |
+
|
| 47 |
+
### Training results
|
| 48 |
+
|
| 49 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| 50 |
+
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
|
| 51 |
+
| 0.3525 | 1.0 | 1859 | 0.2696 | 0.906 |
|
| 52 |
+
| 0.2084 | 2.0 | 3718 | 0.3284 | 0.9143 |
|
| 53 |
+
| 0.1263 | 3.0 | 5577 | 0.4205 | 0.9143 |
|
| 54 |
+
| 0.0734 | 4.0 | 7436 | 0.4688 | 0.9203 |
|
| 55 |
+
| 0.0437 | 5.0 | 9295 | 0.6266 | 0.9173 |
|
| 56 |
+
| 0.0357 | 6.0 | 11154 | 0.6934 | 0.9207 |
|
| 57 |
+
| 0.0264 | 7.0 | 13013 | 0.6947 | 0.92 |
|
| 58 |
+
| 0.0098 | 8.0 | 14872 | 0.6800 | 0.9197 |
|
| 59 |
+
| 0.0104 | 9.0 | 16731 | 0.7393 | 0.923 |
|
| 60 |
+
| 0.0067 | 10.0 | 18590 | 0.7846 | 0.9217 |
|
| 61 |
+
| 0.0034 | 11.0 | 20449 | 0.7450 | 0.922 |
|
| 62 |
+
|
| 63 |
+
|
| 64 |
+
### Framework versions
|
| 65 |
+
|
| 66 |
+
- Transformers 4.21.3
|
| 67 |
+
- Pytorch 1.12.1
|
| 68 |
+
- Datasets 2.5.1
|
| 69 |
+
- Tokenizers 0.11.0
|