Migrate model card from transformers-repo
Browse filesRead announcement at https://discuss.huggingface.co/t/announcement-all-model-cards-will-be-migrated-to-hf-co-model-repos/2755
Original file history: https://github.com/huggingface/transformers/commits/master/model_cards/VictorSanh/roberta-base-finetuned-yelp-polarity/README.md
README.md
ADDED
@@ -0,0 +1,25 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
language: en
|
3 |
+
datasets:
|
4 |
+
- yelp_polarity
|
5 |
+
---
|
6 |
+
|
7 |
+
# RoBERTa-base-finetuned-yelp-polarity
|
8 |
+
|
9 |
+
This is a [RoBERTa-base](https://huggingface.co/roberta-base) checkpoint fine-tuned on binary sentiment classifcation from [Yelp polarity](https://huggingface.co/nlp/viewer/?dataset=yelp_polarity).
|
10 |
+
It gets **98.08%** accuracy on the test set.
|
11 |
+
|
12 |
+
## Hyper-parameters
|
13 |
+
|
14 |
+
We used the following hyper-parameters to train the model on one GPU:
|
15 |
+
```python
|
16 |
+
num_train_epochs = 2.0
|
17 |
+
learning_rate = 1e-05
|
18 |
+
weight_decay = 0.0
|
19 |
+
adam_epsilon = 1e-08
|
20 |
+
max_grad_norm = 1.0
|
21 |
+
per_device_train_batch_size = 32
|
22 |
+
gradient_accumulation_steps = 1
|
23 |
+
warmup_steps = 3500
|
24 |
+
seed = 42
|
25 |
+
```
|