metadata
library_name: transformers
base_model: sengi/lladou-gsm8k-b32
tags:
- generated_from_trainer
model-index:
- name: LLaDA-8B-Instruct
results: []
LLaDA-8B-Instruct
This model is a fine-tuned version of sengi/lladou-gsm8k-b32 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: -9.4135
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: 10
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 40
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 200
- training_steps: 10000
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 12.5223 | 0.001 | 1000 | 19.8564 |
| 15.1946 | 0.002 | 2000 | 20.4100 |
| -13.4932 | 0.3 | 3000 | -12.4603 |
| -12.5083 | 0.4 | 4000 | -9.9804 |
| -11.9398 | 0.5 | 5000 | -9.1448 |
| -15.111 | 1.0532 | 6000 | -9.1216 |
| -16.8137 | 1.1532 | 7000 | -9.8617 |
| -14.6685 | 1.2532 | 8000 | -10.7716 |
| -13.1242 | 1.3532 | 9000 | -9.1976 |
| -12.7972 | 1.4532 | 10000 | -9.4135 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.0