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---
license: mit
base_model: haryoaw/scenario-normal-finetune-clf-data-indolem_sentiment-model-xlm-roberta-base
tags:
- generated_from_trainer
datasets:
- indolem_sentiment
metrics:
- accuracy
- f1
model-index:
- name: scenario-kd_weight_copy-data-indolem_sentiment-model-xlmr_base_trained
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. -->
# scenario-kd_weight_copy-data-indolem_sentiment-model-xlmr_base_trained
This model is a fine-tuned version of [haryoaw/scenario-normal-finetune-clf-data-indolem_sentiment-model-xlm-roberta-base](https://huggingface.co/haryoaw/scenario-normal-finetune-clf-data-indolem_sentiment-model-xlm-roberta-base) on the indolem_sentiment dataset.
It achieves the following results on the evaluation set:
- Loss: 4.8332
- Accuracy: 0.8471
- F1: 0.7336
## 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: 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: 6969
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log | 0.88 | 100 | 7.3908 | 0.7419 | 0.6601 |
| No log | 1.75 | 200 | 3.5626 | 0.8571 | 0.7816 |
| No log | 2.63 | 300 | 8.7677 | 0.7218 | 0.6706 |
| No log | 3.51 | 400 | 4.4989 | 0.8346 | 0.7402 |
| 3.8583 | 4.39 | 500 | 4.6632 | 0.8271 | 0.7273 |
| 3.8583 | 5.26 | 600 | 4.5488 | 0.8496 | 0.7619 |
| 3.8583 | 6.14 | 700 | 4.0955 | 0.8697 | 0.7759 |
| 3.8583 | 7.02 | 800 | 4.4503 | 0.8471 | 0.7404 |
| 3.8583 | 7.89 | 900 | 4.7169 | 0.8346 | 0.7556 |
| 1.2007 | 8.77 | 1000 | 3.8991 | 0.8697 | 0.7739 |
| 1.2007 | 9.65 | 1100 | 5.7272 | 0.8321 | 0.6794 |
| 1.2007 | 10.53 | 1200 | 4.7281 | 0.8596 | 0.7647 |
| 1.2007 | 11.4 | 1300 | 8.4804 | 0.8095 | 0.5682 |
| 1.2007 | 12.28 | 1400 | 4.2305 | 0.8546 | 0.7411 |
| 0.7006 | 13.16 | 1500 | 4.7921 | 0.8371 | 0.7137 |
| 0.7006 | 14.04 | 1600 | 4.6111 | 0.8471 | 0.7215 |
| 0.7006 | 14.91 | 1700 | 4.8332 | 0.8471 | 0.7336 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.13.3
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