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---
library_name: transformers
license: apache-2.0
base_model: AngelRaychev/0.5B-value-iteration_0
tags:
- generated_from_trainer
model-index:
- name: 0.5B-value-iteration_1
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. -->
# 0.5B-value-iteration_1
This model is a fine-tuned version of [AngelRaychev/0.5B-value-iteration_0](https://huggingface.co/AngelRaychev/0.5B-value-iteration_0) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3933
## 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: 1e-06
- train_batch_size: 1024
- eval_batch_size: 1024
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 5.9606 | 0.8130 | 100 | 5.9124 |
| 4.1873 | 1.6260 | 200 | 4.2078 |
| 2.6983 | 2.4390 | 300 | 2.6579 |
| 1.0651 | 3.2520 | 400 | 1.0912 |
| 0.5126 | 4.0650 | 500 | 0.5242 |
| 0.4485 | 4.8780 | 600 | 0.4762 |
| 0.4188 | 5.6911 | 700 | 0.4344 |
| 0.4063 | 6.5041 | 800 | 0.4181 |
| 0.4025 | 7.3171 | 900 | 0.4204 |
| 0.3972 | 8.1301 | 1000 | 0.4092 |
| 0.3981 | 8.9431 | 1100 | 0.4093 |
| 0.3995 | 9.7561 | 1200 | 0.4161 |
| 0.3945 | 10.5691 | 1300 | 0.4101 |
| 0.3933 | 11.3821 | 1400 | 0.4063 |
| 0.3941 | 12.1951 | 1500 | 0.4039 |
| 0.3901 | 13.0081 | 1600 | 0.4029 |
| 0.3908 | 13.8211 | 1700 | 0.4024 |
| 0.3878 | 14.6341 | 1800 | 0.4007 |
| 0.3859 | 15.4472 | 1900 | 0.4011 |
| 0.3882 | 16.2602 | 2000 | 0.4004 |
| 0.3851 | 17.0732 | 2100 | 0.3990 |
| 0.3834 | 17.8862 | 2200 | 0.3991 |
| 0.3842 | 18.6992 | 2300 | 0.3979 |
| 0.3838 | 19.5122 | 2400 | 0.3971 |
| 0.3846 | 20.3252 | 2500 | 0.3971 |
| 0.381 | 21.1382 | 2600 | 0.3978 |
| 0.3837 | 21.9512 | 2700 | 0.3975 |
| 0.3805 | 22.7642 | 2800 | 0.3957 |
| 0.3811 | 23.5772 | 2900 | 0.3973 |
| 0.3814 | 24.3902 | 3000 | 0.3953 |
| 0.3821 | 25.2033 | 3100 | 0.3957 |
| 0.3813 | 26.0163 | 3200 | 0.3951 |
| 0.3794 | 26.8293 | 3300 | 0.3953 |
| 0.3824 | 27.6423 | 3400 | 0.3945 |
| 0.3779 | 28.4553 | 3500 | 0.3944 |
| 0.3796 | 29.2683 | 3600 | 0.3953 |
| 0.3793 | 30.0813 | 3700 | 0.3948 |
| 0.3809 | 30.8943 | 3800 | 0.3949 |
| 0.3796 | 31.7073 | 3900 | 0.3946 |
| 0.3785 | 32.5203 | 4000 | 0.3939 |
| 0.3791 | 33.3333 | 4100 | 0.3940 |
| 0.3791 | 34.1463 | 4200 | 0.3942 |
| 0.3785 | 34.9593 | 4300 | 0.3937 |
| 0.3784 | 35.7724 | 4400 | 0.3939 |
| 0.3789 | 36.5854 | 4500 | 0.3941 |
| 0.3775 | 37.3984 | 4600 | 0.3940 |
| 0.3784 | 38.2114 | 4700 | 0.3939 |
| 0.3795 | 39.0244 | 4800 | 0.3940 |
| 0.3768 | 39.8374 | 4900 | 0.3938 |
| 0.3789 | 40.6504 | 5000 | 0.3938 |
| 0.378 | 41.4634 | 5100 | 0.3939 |
| 0.3794 | 42.2764 | 5200 | 0.3938 |
| 0.3792 | 43.0894 | 5300 | 0.3941 |
| 0.3786 | 43.9024 | 5400 | 0.3936 |
| 0.3785 | 44.7154 | 5500 | 0.3938 |
| 0.3793 | 45.5285 | 5600 | 0.3933 |
| 0.3782 | 46.3415 | 5700 | 0.3936 |
| 0.3789 | 47.1545 | 5800 | 0.3956 |
| 0.3765 | 47.9675 | 5900 | 0.3936 |
| 0.3781 | 48.7805 | 6000 | 0.3946 |
| 0.3805 | 49.5935 | 6100 | 0.3947 |
### Framework versions
- Transformers 4.51.2
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
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