---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased-distilled-squad
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: distilbert-base-uncased-distilled-squad_07112024T120722
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# distilbert-base-uncased-distilled-squad_07112024T120722

This model is a fine-tuned version of [distilbert/distilbert-base-uncased-distilled-squad](https://huggingface.co/distilbert/distilbert-base-uncased-distilled-squad) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7930
- F1: 0.7643
- Learning Rate: 0.0

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Rate   |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| No log        | 1.0   | 121  | 1.1749          | 0.5577 | 0.0000 |
| No log        | 2.0   | 242  | 0.9801          | 0.6593 | 0.0000 |
| No log        | 3.0   | 363  | 0.9184          | 0.6951 | 0.0000 |
| No log        | 4.0   | 484  | 0.8064          | 0.7480 | 0.0000 |
| 0.9941        | 5.0   | 605  | 0.7930          | 0.7643 | 0.0000 |
| 0.9941        | 6.0   | 726  | 0.8313          | 0.7793 | 0.0000 |
| 0.9941        | 7.0   | 847  | 0.8955          | 0.7814 | 0.0000 |
| 0.9941        | 8.0   | 968  | 0.9010          | 0.7963 | 0.0000 |
| 0.3299        | 9.0   | 1089 | 0.9855          | 0.7945 | 0.0000 |
| 0.3299        | 10.0  | 1210 | 0.9753          | 0.8036 | 0.0000 |
| 0.3299        | 11.0  | 1331 | 1.0115          | 0.8095 | 0.0000 |
| 0.3299        | 12.0  | 1452 | 1.0508          | 0.8052 | 7e-06  |
| 0.0991        | 13.0  | 1573 | 1.1102          | 0.8125 | 0.0000 |
| 0.0991        | 14.0  | 1694 | 1.1321          | 0.8146 | 0.0000 |
| 0.0991        | 15.0  | 1815 | 1.2166          | 0.8085 | 3e-06  |
| 0.0991        | 16.0  | 1936 | 1.1935          | 0.8109 | 0.0000 |
| 0.0349        | 17.0  | 2057 | 1.2277          | 0.8074 | 0.0000 |
| 0.0349        | 18.0  | 2178 | 1.2145          | 0.8091 | 5e-07  |
| 0.0349        | 19.0  | 2299 | 1.2306          | 0.8082 | 1e-07  |
| 0.0349        | 20.0  | 2420 | 1.2334          | 0.8080 | 0.0    |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.19.1