update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,77 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: mit
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
metrics:
|
| 6 |
+
- accuracy
|
| 7 |
+
model-index:
|
| 8 |
+
- name: tluo_xml_roberta_base_amazon_review_sentiment_v4
|
| 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 |
+
# tluo_xml_roberta_base_amazon_review_sentiment_v4
|
| 16 |
+
|
| 17 |
+
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
|
| 18 |
+
It achieves the following results on the evaluation set:
|
| 19 |
+
- Loss: 0.9589
|
| 20 |
+
- Accuracy: 0.6137
|
| 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: 1.5745609276104923e-05
|
| 40 |
+
- train_batch_size: 4
|
| 41 |
+
- eval_batch_size: 4
|
| 42 |
+
- seed: 25
|
| 43 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 44 |
+
- lr_scheduler_type: linear
|
| 45 |
+
- num_epochs: 3
|
| 46 |
+
- mixed_precision_training: Native AMP
|
| 47 |
+
|
| 48 |
+
### Training results
|
| 49 |
+
|
| 50 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| 51 |
+
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
|
| 52 |
+
| 1.1074 | 0.17 | 5000 | 1.0468 | 0.5493 |
|
| 53 |
+
| 1.0461 | 0.33 | 10000 | 1.0222 | 0.558 |
|
| 54 |
+
| 1.0245 | 0.5 | 15000 | 0.9776 | 0.5793 |
|
| 55 |
+
| 0.9876 | 0.67 | 20000 | 1.0327 | 0.571 |
|
| 56 |
+
| 1.0073 | 0.83 | 25000 | 0.9695 | 0.5807 |
|
| 57 |
+
| 0.9808 | 1.0 | 30000 | 1.0077 | 0.5857 |
|
| 58 |
+
| 0.9399 | 1.17 | 35000 | 1.0113 | 0.6043 |
|
| 59 |
+
| 0.8944 | 1.33 | 40000 | 0.9534 | 0.5947 |
|
| 60 |
+
| 0.908 | 1.5 | 45000 | 1.0155 | 0.5947 |
|
| 61 |
+
| 0.9238 | 1.67 | 50000 | 0.9813 | 0.597 |
|
| 62 |
+
| 0.8699 | 1.83 | 55000 | 0.9646 | 0.6027 |
|
| 63 |
+
| 0.8829 | 2.0 | 60000 | 0.9589 | 0.6137 |
|
| 64 |
+
| 0.8214 | 2.17 | 65000 | 1.0378 | 0.6017 |
|
| 65 |
+
| 0.8052 | 2.33 | 70000 | 1.0080 | 0.6003 |
|
| 66 |
+
| 0.7807 | 2.5 | 75000 | 1.0830 | 0.604 |
|
| 67 |
+
| 0.7927 | 2.67 | 80000 | 1.0225 | 0.6007 |
|
| 68 |
+
| 0.8358 | 2.83 | 85000 | 0.9989 | 0.5997 |
|
| 69 |
+
| 0.7899 | 3.0 | 90000 | 1.0108 | 0.6023 |
|
| 70 |
+
|
| 71 |
+
|
| 72 |
+
### Framework versions
|
| 73 |
+
|
| 74 |
+
- Transformers 4.24.0
|
| 75 |
+
- Pytorch 1.12.1+cu113
|
| 76 |
+
- Datasets 2.7.1
|
| 77 |
+
- Tokenizers 0.13.2
|