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---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased-finetuned-sst-2-english
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: distilbert-base-uncased-finetuned-sst-2-english_07112024T125645
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-finetuned-sst-2-english_07112024T125645
This model is a fine-tuned version of [distilbert/distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert/distilbert-base-uncased-finetuned-sst-2-english) on the MR Analysis Phase-3 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5776
- F1: 0.8426
- 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 | 141 | 1.1776 | 0.5721 | 0.0000 |
| No log | 2.0 | 282 | 0.9785 | 0.6619 | 0.0000 |
| No log | 3.0 | 423 | 0.8326 | 0.7194 | 0.0000 |
| 1.1084 | 4.0 | 564 | 0.6920 | 0.7808 | 0.0000 |
| 1.1084 | 5.0 | 705 | 0.6907 | 0.7973 | 0.0000 |
| 1.1084 | 6.0 | 846 | 0.6107 | 0.8284 | 0.0000 |
| 1.1084 | 7.0 | 987 | 0.5776 | 0.8426 | 0.0000 |
| 0.4572 | 8.0 | 1128 | 0.6100 | 0.8523 | 0.0000 |
| 0.4572 | 9.0 | 1269 | 0.6279 | 0.8570 | 0.0000 |
| 0.4572 | 10.0 | 1410 | 0.6638 | 0.8587 | 0.0000 |
| 0.1637 | 11.0 | 1551 | 0.7340 | 0.8568 | 0.0000 |
| 0.1637 | 12.0 | 1692 | 0.7564 | 0.8596 | 7e-06 |
| 0.1637 | 13.0 | 1833 | 0.8077 | 0.8568 | 0.0000 |
| 0.1637 | 14.0 | 1974 | 0.7234 | 0.8667 | 0.0000 |
| 0.069 | 15.0 | 2115 | 0.7535 | 0.8664 | 3e-06 |
| 0.069 | 16.0 | 2256 | 0.7818 | 0.8659 | 0.0000 |
| 0.069 | 17.0 | 2397 | 0.8064 | 0.8646 | 0.0000 |
| 0.0376 | 18.0 | 2538 | 0.8203 | 0.8626 | 5e-07 |
| 0.0376 | 19.0 | 2679 | 0.8233 | 0.8629 | 1e-07 |
| 0.0376 | 20.0 | 2820 | 0.8235 | 0.8632 | 0.0 |
### Testing Results
| class | precision | recall | f1-score |
|:------------------------:|:---------:|:------:|:--------:|
| change_request | 0.918 | 0.651 | 0.762 |
| discussion_participation | 0.839 | 0.882 | 0.860 |
| discussion_trigger | 0.879 | 0.902 | 0.890 |
| acknowledgement | 0.847 | 0.920 | 0.882 |
| critical | 0.686 | 0.940 | 0.793 |
| reference | 0.802 | 0.947 | 0.869 |
| ----------- | ---------- | --------| --------- |
| **accuracy** | | | 0.828 |
| **macro avg** | 0.828 | 0.874 | 0.843 |
| **weighted avg** | 0.845 | 0.828 | 0.825 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.19.1
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