metadata
library_name: transformers
base_model: RefalMachine/ruadapt_qwen2.5_3B_ext_u48_mean_init
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ruadapt_qwen2.5_3B_ext_u48_full_lr3e4_bs256
results: []
ruadapt_qwen2.5_3B_ext_u48_full_lr3e4_bs256
This model is a fine-tuned version of RefalMachine/ruadapt_qwen2.5_3B_ext_u48_mean_init on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.4832
- Accuracy: 0.4983
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: 0.0003
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 64
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.0001 | 1 | 5.8817 | 0.3107 |
| 2.6497 | 0.1765 | 2000 | 2.5180 | 0.4939 |
| 2.6174 | 0.3531 | 4000 | 2.4940 | 0.4966 |
| 2.5972 | 0.5296 | 6000 | 2.4866 | 0.4977 |
| 2.6022 | 0.7062 | 8000 | 2.4836 | 0.4982 |
| 2.5999 | 0.8827 | 10000 | 2.4831 | 0.4983 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.3.0a0+6ddf5cf85e.nv24.04
- Datasets 2.18.0
- Tokenizers 0.20.1