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---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base_lr0.0001_seed42_basic_original_kin-amh-eng_train
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. -->
# xlm-roberta-base_lr0.0001_seed42_basic_original_kin-amh-eng_train
This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0399
- Spearman Corr: 0.0444
## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Spearman Corr |
|:-------------:|:-----:|:----:|:---------------:|:-------------:|
| No log | 1.75 | 200 | 0.0384 | -0.0298 |
| 0.0606 | 3.51 | 400 | 0.0428 | 0.0555 |
| 0.0542 | 5.26 | 600 | 0.0399 | 0.1268 |
| 0.0522 | 7.02 | 800 | 0.0373 | 0.2132 |
| 0.0519 | 8.77 | 1000 | 0.0399 | 0.0780 |
| 0.0516 | 10.53 | 1200 | 0.0391 | nan |
| 0.051 | 12.28 | 1400 | 0.0380 | -0.0558 |
| 0.0505 | 14.04 | 1600 | 0.0375 | 0.0632 |
| 0.0505 | 15.79 | 1800 | 0.0390 | 0.0344 |
| 0.0505 | 17.54 | 2000 | 0.0395 | 0.0575 |
| 0.0498 | 19.3 | 2200 | 0.0397 | 0.0553 |
| 0.0494 | 21.05 | 2400 | 0.0381 | 0.0810 |
| 0.0492 | 22.81 | 2600 | 0.0383 | nan |
| 0.0489 | 24.56 | 2800 | 0.0399 | 0.0444 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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