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---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- f1
model-index:
- name: results
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: massive
type: massive
config: en-US
split: test
args: en-US
metrics:
- name: F1
type: f1
value: 0.9734295558770142
---
<!-- 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. -->
# results
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0231
- F1: 0.9734
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.8235 | 0.5 | 185 | 3.7551 | 0.0022 |
| 3.5949 | 0.99 | 370 | 3.1246 | 0.0454 |
| 2.8705 | 1.49 | 555 | 2.4379 | 0.1543 |
| 2.3444 | 1.99 | 740 | 1.7732 | 0.2967 |
| 1.7151 | 2.49 | 925 | 1.2983 | 0.4403 |
| 1.3959 | 2.98 | 1110 | 0.9965 | 0.5490 |
| 0.9919 | 3.48 | 1295 | 0.7098 | 0.6880 |
| 0.9495 | 3.98 | 1480 | 0.5798 | 0.7014 |
| 0.6 | 4.48 | 1665 | 0.4419 | 0.7408 |
| 0.5952 | 4.97 | 1850 | 0.3653 | 0.7522 |
| 0.3715 | 5.47 | 2035 | 0.3077 | 0.7957 |
| 0.3783 | 5.97 | 2220 | 0.2050 | 0.8453 |
| 0.196 | 6.47 | 2405 | 0.1532 | 0.8386 |
| 0.22 | 6.96 | 2590 | 0.0968 | 0.8871 |
| 0.1117 | 7.46 | 2775 | 0.0725 | 0.9057 |
| 0.1065 | 7.96 | 2960 | 0.0458 | 0.9265 |
| 0.0644 | 8.45 | 3145 | 0.0378 | 0.9336 |
| 0.0526 | 8.95 | 3330 | 0.0324 | 0.9616 |
| 0.0521 | 9.45 | 3515 | 0.0251 | 0.9708 |
| 0.0302 | 9.95 | 3700 | 0.0231 | 0.9734 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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