|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: answerdotai/ModernBERT-large |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: modernbert-dllm-tulu |
|
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. --> |
|
|
|
# modernbert-dllm-tulu |
|
|
|
This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.6432 |
|
|
|
## 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 |
|
- distributed_type: multi-GPU |
|
- num_devices: 4 |
|
- total_train_batch_size: 128 |
|
- total_eval_batch_size: 128 |
|
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
- lr_scheduler_type: linear |
|
- num_epochs: 1 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:------:|:----:|:---------------:| |
|
| No log | 0.0332 | 200 | 1.7948 | |
|
| No log | 0.0664 | 400 | 1.7504 | |
|
| 1.7964 | 0.0997 | 600 | 1.7230 | |
|
| 1.7964 | 0.1329 | 800 | 1.7046 | |
|
| 1.717 | 0.1661 | 1000 | 1.6923 | |
|
| 1.717 | 0.1993 | 1200 | 1.6827 | |
|
| 1.717 | 0.2326 | 1400 | 1.6752 | |
|
| 1.6662 | 0.2658 | 1600 | 1.6689 | |
|
| 1.6662 | 0.2990 | 1800 | 1.6638 | |
|
| 1.6667 | 0.3322 | 2000 | 1.6601 | |
|
| 1.6667 | 0.3654 | 2200 | 1.6574 | |
|
| 1.6667 | 0.3987 | 2400 | 1.6544 | |
|
| 1.6626 | 0.4319 | 2600 | 1.6525 | |
|
| 1.6626 | 0.4651 | 2800 | 1.6505 | |
|
| 1.6472 | 0.4983 | 3000 | 1.6493 | |
|
| 1.6472 | 0.5316 | 3200 | 1.6479 | |
|
| 1.6472 | 0.5648 | 3400 | 1.6469 | |
|
| 1.6354 | 0.5980 | 3600 | 1.6460 | |
|
| 1.6354 | 0.6312 | 3800 | 1.6454 | |
|
| 1.6457 | 0.6645 | 4000 | 1.6448 | |
|
| 1.6457 | 0.6977 | 4200 | 1.6445 | |
|
| 1.6457 | 0.7309 | 4400 | 1.6440 | |
|
| 1.6404 | 0.7641 | 4600 | 1.6437 | |
|
| 1.6404 | 0.7973 | 4800 | 1.6436 | |
|
| 1.6472 | 0.8306 | 5000 | 1.6435 | |
|
| 1.6472 | 0.8638 | 5200 | 1.6434 | |
|
| 1.6472 | 0.8970 | 5400 | 1.6433 | |
|
| 1.6394 | 0.9302 | 5600 | 1.6433 | |
|
| 1.6394 | 0.9635 | 5800 | 1.6432 | |
|
| 1.6313 | 0.9967 | 6000 | 1.6432 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.53.0 |
|
- Pytorch 2.7.1+cu126 |
|
- Datasets 3.6.0 |
|
- Tokenizers 0.21.2 |
|
|