Instructions to use textattack/bert-base-uncased-MRPC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/bert-base-uncased-MRPC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/bert-base-uncased-MRPC")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/bert-base-uncased-MRPC") model = AutoModelForSequenceClassification.from_pretrained("textattack/bert-base-uncased-MRPC") - Inference
- Notebooks
- Google Colab
- Kaggle
Update eval_results_mrpc.txt
Browse files- eval_results_mrpc.txt +5 -0
eval_results_mrpc.txt
ADDED
|
@@ -0,0 +1,5 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
eval_loss = 0.4741157080445971
|
| 2 |
+
eval_acc = 0.8014705882352942
|
| 3 |
+
eval_f1 = 0.8691437802907915
|
| 4 |
+
eval_acc_and_f1 = 0.8353071842630428
|
| 5 |
+
epoch = 3.0
|