transformers tensorboard safetensors distilbert question-answering generated_from_trainer base_model:distilbert-base-uncased license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-finetuned-squad
  results: []
---

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# distilbert-base-uncased-finetuned-squad

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the Squad dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3978

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 65   | 3.4665          |
| No log        | 2.0   | 130  | 2.8392          |
| No log        | 3.0   | 195  | 2.4838          |
| No log        | 4.0   | 260  | 2.3667          |
| No log        | 5.0   | 325  | 2.3424          |
| No log        | 6.0   | 390  | 2.2847          |
| No log        | 7.0   | 455  | 2.3560          |
| 2.1356        | 8.0   | 520  | 2.3636          |
| 2.1356        | 9.0   | 585  | 2.3655          |
| 2.1356        | 10.0  | 650  | 2.3978          |

### Usage

```
question = "What is rama's friend name?"
context = "My name is rama. My friend name is raju."
from transformers import pipeline

question_answerer = pipeline("question-answering", model="likhith231/distilbert-base-uncased-finetuned-squad")
question_answerer(question=question, context=context)
```


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1
