Text Classification
Transformers
TensorFlow
distilbert
generated_from_keras_callback
text-embeddings-inference
Instructions to use Apv/Distilbert_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Apv/Distilbert_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Apv/Distilbert_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Apv/Distilbert_v1") model = AutoModelForSequenceClassification.from_pretrained("Apv/Distilbert_v1") - Notebooks
- Google Colab
- Kaggle
Training in progress epoch 4
Browse files
README.md
CHANGED
|
@@ -14,10 +14,10 @@ probably proofread and complete it, then remove this comment. -->
|
|
| 14 |
|
| 15 |
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
|
| 16 |
It achieves the following results on the evaluation set:
|
| 17 |
-
- Train Loss: 0.
|
| 18 |
- Validation Loss: 0.5875
|
| 19 |
- Train Accuracy: 0.7820
|
| 20 |
-
- Epoch:
|
| 21 |
|
| 22 |
## Model description
|
| 23 |
|
|
@@ -47,6 +47,7 @@ The following hyperparameters were used during training:
|
|
| 47 |
| 0.5724 | 0.5875 | 0.7820 | 1 |
|
| 48 |
| 0.5629 | 0.5875 | 0.7820 | 2 |
|
| 49 |
| 0.5601 | 0.5875 | 0.7820 | 3 |
|
|
|
|
| 50 |
|
| 51 |
|
| 52 |
### Framework versions
|
|
|
|
| 14 |
|
| 15 |
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
|
| 16 |
It achieves the following results on the evaluation set:
|
| 17 |
+
- Train Loss: 0.5605
|
| 18 |
- Validation Loss: 0.5875
|
| 19 |
- Train Accuracy: 0.7820
|
| 20 |
+
- Epoch: 4
|
| 21 |
|
| 22 |
## Model description
|
| 23 |
|
|
|
|
| 47 |
| 0.5724 | 0.5875 | 0.7820 | 1 |
|
| 48 |
| 0.5629 | 0.5875 | 0.7820 | 2 |
|
| 49 |
| 0.5601 | 0.5875 | 0.7820 | 3 |
|
| 50 |
+
| 0.5605 | 0.5875 | 0.7820 | 4 |
|
| 51 |
|
| 52 |
|
| 53 |
### Framework versions
|