Instructions to use ruanchaves/mdeberta-v3-base-faquad-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ruanchaves/mdeberta-v3-base-faquad-nli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ruanchaves/mdeberta-v3-base-faquad-nli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ruanchaves/mdeberta-v3-base-faquad-nli") model = AutoModelForSequenceClassification.from_pretrained("ruanchaves/mdeberta-v3-base-faquad-nli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
b0070aa
1
Parent(s): e41802d
Upload train_results.json with huggingface_hub
Browse files- train_results.json +8 -0
train_results.json
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"epoch": 20.0,
|
| 3 |
+
"train_loss": 0.056036626369907305,
|
| 4 |
+
"train_runtime": 3116.2149,
|
| 5 |
+
"train_samples": 3128,
|
| 6 |
+
"train_samples_per_second": 20.076,
|
| 7 |
+
"train_steps_per_second": 1.252
|
| 8 |
+
}
|