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---
base_model: RefalMachine/mistral_extended_darulm_20_05_24_part1-2_32000_bpe_mean_init_03_07_24
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mistral_extended_darulm_20_05_24_part1-2_32000_bpe_part1_lr2e5_bs256
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. -->
# mistral_extended_darulm_20_05_24_part1-2_32000_bpe_part1_lr2e5_bs256
This model is a fine-tuned version of [RefalMachine/mistral_extended_darulm_20_05_24_part1-2_32000_bpe_mean_init_03_07_24](https://huggingface.co/RefalMachine/mistral_extended_darulm_20_05_24_part1-2_32000_bpe_mean_init_03_07_24) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2338
- Accuracy: 0.5418
## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 32
- total_train_batch_size: 128
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.6021 | 0.09 | 2000 | 2.3285 | 0.5305 |
| 2.5355 | 0.18 | 4000 | 2.2744 | 0.5365 |
| 2.5063 | 0.27 | 6000 | 2.2538 | 0.5391 |
| 2.4939 | 0.36 | 8000 | 2.2441 | 0.5402 |
| 2.463 | 0.45 | 10000 | 2.2385 | 0.5410 |
| 2.4559 | 0.54 | 12000 | 2.2359 | 0.5414 |
| 2.5186 | 0.63 | 14000 | 2.2347 | 0.5415 |
| 2.4755 | 0.73 | 16000 | 2.2340 | 0.5416 |
| 2.4813 | 0.82 | 18000 | 2.2338 | 0.5417 |
| 2.4797 | 0.91 | 20000 | 2.2338 | 0.5418 |
| 2.4525 | 1.0 | 22000 | 2.2338 | 0.5418 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.3.0a0+6ddf5cf85e.nv24.04
- Datasets 2.18.0
- Tokenizers 0.15.2
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