
# Model Card for Model ID

This model is a fine-tuned version of distilbert-base-cased on SQuAD dataset. It achieves the following results on the evaluation set:

- Train Loss: 0.9125
- Validation Loss: 1.0106
- Epoch: 2
- Training Accuracy: 0.7709
- Validation Accuracy: 0.7613

After using regularization and finetuning our model, here’s how it is performing:

- Train Loss: 0.7615
- Validation Loss: 0.6138
- Epoch: 4
- Training Accuracy: 0.8102
- Validation Accuracy: 0.8210


{}
transformers tf distilbert question-answering endpoints_compatible region:us
TAGS
#transformers #tf #distilbert #question-answering #endpoints_compatible #region-us 


# Model Card for Model ID

This model is a fine-tuned version of distilbert-base-cased on SQuAD dataset. It achieves the following results on the evaluation set:

- Train Loss: 0.9125
- Validation Loss: 1.0106
- Epoch: 2
- Training Accuracy: 0.7709
- Validation Accuracy: 0.7613

After using regularization and finetuning our model, here’s how it is performing:

- Train Loss: 0.7615
- Validation Loss: 0.6138
- Epoch: 4
- Training Accuracy: 0.8102
- Validation Accuracy: 0.8210


# Model Card for Model ID

This model is a fine-tuned version of distilbert-base-cased on SQuAD dataset. It achieves the following results on the evaluation set:

- Train Loss: 0.9125
- Validation Loss: 1.0106
- Epoch: 2
- Training Accuracy: 0.7709
- Validation Accuracy: 0.7613

After using regularization and finetuning our model, here’s how it is performing:

- Train Loss: 0.7615
- Validation Loss: 0.6138
- Epoch: 4
- Training Accuracy: 0.8102
- Validation Accuracy: 0.8210
TAGS
#transformers #tf #distilbert #question-answering #endpoints_compatible #region-us 
 # Model Card for Model ID

This model is a fine-tuned version of distilbert-base-cased on SQuAD dataset. It achieves the following results on the evaluation set:

- Train Loss: 0.9125
- Validation Loss: 1.0106
- Epoch: 2
- Training Accuracy: 0.7709
- Validation Accuracy: 0.7613

After using regularization and finetuning our model, here’s how it is performing:

- Train Loss: 0.7615
- Validation Loss: 0.6138
- Epoch: 4
- Training Accuracy: 0.8102
- Validation Accuracy: 0.8210
TAGS
#transformers #tf #distilbert #question-answering #endpoints_compatible #region-us 
# Model Card for Model ID

This model is a fine-tuned version of distilbert-base-cased on SQuAD dataset. It achieves the following results on the evaluation set:

- Train Loss: 0.9125
- Validation Loss: 1.0106
- Epoch: 2
- Training Accuracy: 0.7709
- Validation Accuracy: 0.7613

After using regularization and finetuning our model, here’s how it is performing:

- Train Loss: 0.7615
- Validation Loss: 0.6138
- Epoch: 4
- Training Accuracy: 0.8102
- Validation Accuracy: 0.8210