---
license: apache-2.0
base_model: Qwen/Qwen2-1.5B
tags:
- generated_from_trainer
model-index:
- name: outputs/out
  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. -->

[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.4.1`
```yaml
base_model: Qwen/Qwen2-1.5B
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

trust_remote_code: true

load_in_8bit: false
load_in_4bit: false
strict: false

datasets:
  - path: civit-slop-combined.jsonl
    type: alpaca

chat_template: chatml

dataset_prepared_path:
val_set_size: 0.05
output_dir: ./outputs/out
sequence_len: 2048
sample_packing: true
eval_sample_packing: true
pad_to_sequence_len: true

adapter:
lora_model_dir:
lora_r:
lora_alpha:
lora_dropout:
lora_target_linear: true
lora_fan_in_fan_out:

wandb_project: Mango-SDprompt-qwen
wandb_entity:
wandb_watch:
wandb_name: qwen1.5b-2
wandb_log_model:

gradient_accumulation_steps: 4
micro_batch_size: 1
num_epochs: 4
optimizer: adamw_torch
lr_scheduler: cosine
learning_rate: 0.0002

train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: true

gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: false
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_ratio: 0.2
evals_per_epoch: 4
saves_per_epoch: 1
debug:
#deepspeed: deepspeed_configs/zero2.json
#deepspeed: /training/axolotl/axolotl/deepspeed_configs/zero2.json
weight_decay: 0.0
#fsdp:
#fsdp_config:
#  fsdp_limit_all_gathers: true
#  fsdp_sync_module_states: true
#  fsdp_offload_params: true
#  fsdp_use_orig_params: false
#  fsdp_cpu_ram_efficient_loading: true
#  fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
#  fsdp_transformer_layer_cls_to_wrap: Qwen2DecoderLayer
#  fsdp_state_dict_type: FULL_STATE_DICT
special_tokens:

```

</details><br>

# outputs/out

This model is a fine-tuned version of [Qwen/Qwen2-1.5B](https://huggingface.co./Qwen/Qwen2-1.5B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.9785

## 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: 0.0002
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 312
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 3.4279        | 0.0024 | 1    | 4.1321          |
| 2.6008        | 0.2516 | 106  | 3.4527          |
| 2.7346        | 0.5033 | 212  | 3.6512          |
| 3.0676        | 0.7549 | 318  | 3.8178          |
| 3.2084        | 1.0065 | 424  | 3.7616          |
| 2.6999        | 1.2368 | 530  | 3.8072          |
| 2.3664        | 1.4884 | 636  | 3.7223          |
| 3.0722        | 1.7401 | 742  | 3.6350          |
| 2.7612        | 1.9917 | 848  | 3.5670          |
| 1.2179        | 2.2226 | 954  | 4.0217          |
| 1.5539        | 2.4742 | 1060 | 3.9957          |
| 1.255         | 2.7258 | 1166 | 4.0404          |
| 0.9165        | 2.9774 | 1272 | 4.0294          |
| 0.1785        | 3.2089 | 1378 | 4.9794          |
| 0.1931        | 3.4605 | 1484 | 4.9763          |
| 0.3729        | 3.7122 | 1590 | 4.9785          |


### Framework versions

- Transformers 4.44.0.dev0
- Pytorch 2.1.2+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1