File size: 2,584 Bytes
51554ed |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 |
---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base_lr0.0001_seed42_basic_original_amh-hau-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_amh-hau-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: 0.0468
- Spearman Corr: 0.0355
## 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 | 1.55 | 200 | 0.0533 | -0.1261 |
| 0.0648 | 3.1 | 400 | 0.0450 | 0.0883 |
| 0.0593 | 4.65 | 600 | 0.0551 | nan |
| 0.0584 | 6.2 | 800 | 0.0453 | 0.0647 |
| 0.0584 | 7.75 | 1000 | 0.0535 | 0.1302 |
| 0.0584 | 9.3 | 1200 | 0.0447 | 0.1247 |
| 0.0564 | 10.85 | 1400 | 0.0568 | 0.0145 |
| 0.0564 | 12.4 | 1600 | 0.0447 | nan |
| 0.056 | 13.95 | 1800 | 0.0491 | 0.0365 |
| 0.056 | 15.5 | 2000 | 0.0472 | nan |
| 0.0564 | 17.05 | 2200 | 0.0473 | nan |
| 0.0555 | 18.6 | 2400 | 0.0457 | nan |
| 0.0555 | 20.16 | 2600 | 0.0472 | -0.0083 |
| 0.0555 | 21.71 | 2800 | 0.0473 | nan |
| 0.055 | 23.26 | 3000 | 0.0447 | 0.0283 |
| 0.0549 | 24.81 | 3200 | 0.0468 | 0.0355 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
|