metadata
base_model: nreimers/mMiniLMv2-L6-H384-distilled-from-XLMR-Large
tags:
- generated_from_trainer
model-index:
- name: trainRanker_test_test
results: []
trainRanker_test_test
This model is a fine-tuned version of nreimers/mMiniLMv2-L6-H384-distilled-from-XLMR-Large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4322
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: 0.5
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.6929 | 0.16 | 200 | 0.6925 |
| 0.6907 | 0.32 | 400 | 0.5492 |
| 0.4975 | 0.48 | 600 | 0.4721 |
| 0.4584 | 0.64 | 800 | 0.4444 |
| 0.4596 | 0.8 | 1000 | 0.4309 |
| 0.4431 | 0.96 | 1200 | 0.4338 |
| 0.4233 | 1.12 | 1400 | 0.4322 |
| 0.4451 | 1.28 | 1600 | 0.4322 |
| 0.4346 | 1.44 | 1800 | 0.4322 |
| 0.4239 | 1.6 | 2000 | 0.4322 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1