---
library_name: transformers
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: llama_1b_step2_batch_v2
  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. -->

# llama_1b_step2_batch_v2

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3338

## 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: 2
- eval_batch_size: 40
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.9373        | 0.0341 | 50   | 0.8757          |
| 0.6838        | 0.0682 | 100  | 0.7815          |
| 0.7189        | 0.1023 | 150  | 0.7197          |
| 0.5827        | 0.1364 | 200  | 0.6686          |
| 0.5084        | 0.1704 | 250  | 0.6180          |
| 0.5357        | 0.2045 | 300  | 0.5858          |
| 0.4738        | 0.2386 | 350  | 0.5618          |
| 0.5091        | 0.2727 | 400  | 0.5337          |
| 0.3793        | 0.3068 | 450  | 0.5149          |
| 0.5388        | 0.3409 | 500  | 0.4985          |
| 0.4726        | 0.3750 | 550  | 0.4801          |
| 0.5348        | 0.4091 | 600  | 0.4632          |
| 0.4644        | 0.4432 | 650  | 0.4477          |
| 0.4033        | 0.4772 | 700  | 0.4367          |
| 0.4283        | 0.5113 | 750  | 0.4309          |
| 0.5275        | 0.5454 | 800  | 0.4201          |
| 0.4633        | 0.5795 | 850  | 0.4115          |
| 0.3312        | 0.6136 | 900  | 0.4038          |
| 0.4768        | 0.6477 | 950  | 0.3969          |
| 0.4401        | 0.6818 | 1000 | 0.3924          |
| 0.3125        | 0.7159 | 1050 | 0.3882          |
| 0.3651        | 0.7500 | 1100 | 0.3820          |
| 0.354         | 0.7840 | 1150 | 0.3770          |
| 0.3525        | 0.8181 | 1200 | 0.3701          |
| 0.4069        | 0.8522 | 1250 | 0.3659          |
| 0.2806        | 0.8863 | 1300 | 0.3613          |
| 0.3593        | 0.9204 | 1350 | 0.3584          |
| 0.3393        | 0.9545 | 1400 | 0.3540          |
| 0.3114        | 0.9886 | 1450 | 0.3504          |
| 0.2571        | 1.0228 | 1500 | 0.3556          |
| 0.2991        | 1.0569 | 1550 | 0.3531          |
| 0.2445        | 1.0910 | 1600 | 0.3512          |
| 0.2865        | 1.1251 | 1650 | 0.3520          |
| 0.2146        | 1.1592 | 1700 | 0.3492          |
| 0.2469        | 1.1933 | 1750 | 0.3481          |
| 0.2927        | 1.2274 | 1800 | 0.3474          |
| 0.2797        | 1.2615 | 1850 | 0.3454          |
| 0.247         | 1.2956 | 1900 | 0.3455          |
| 0.2208        | 1.3296 | 1950 | 0.3433          |
| 0.2396        | 1.3637 | 2000 | 0.3420          |
| 0.252         | 1.3978 | 2050 | 0.3407          |
| 0.2296        | 1.4319 | 2100 | 0.3387          |
| 0.2349        | 1.4660 | 2150 | 0.3391          |
| 0.2408        | 1.5001 | 2200 | 0.3374          |
| 0.236         | 1.5342 | 2250 | 0.3376          |
| 0.1969        | 1.5683 | 2300 | 0.3375          |
| 0.2513        | 1.6024 | 2350 | 0.3368          |
| 0.2619        | 1.6364 | 2400 | 0.3360          |
| 0.3016        | 1.6705 | 2450 | 0.3351          |
| 0.2345        | 1.7046 | 2500 | 0.3352          |
| 0.2474        | 1.7387 | 2550 | 0.3347          |
| 0.2475        | 1.7728 | 2600 | 0.3343          |
| 0.2627        | 1.8069 | 2650 | 0.3342          |
| 0.2381        | 1.8410 | 2700 | 0.3340          |
| 0.2984        | 1.8751 | 2750 | 0.3338          |
| 0.2434        | 1.9092 | 2800 | 0.3338          |
| 0.2608        | 1.9432 | 2850 | 0.3338          |
| 0.2526        | 1.9773 | 2900 | 0.3338          |


### Framework versions

- Transformers 4.46.0
- Pytorch 2.1.0+cu118
- Datasets 3.0.2
- Tokenizers 0.20.1