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---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen2-7B
tags:
- generated_from_trainer
model-index:
- name: outputs/out
results: []
---
I FUCKING ADDED BAD DATA MADE TO BE USED FOR KTO TO THE TRAIN BY ACCIDENT HAHAHA
<!-- 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. -->
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<details><summary>See axolotl config</summary>
axolotl version: `0.4.1`
```yaml
base_model: Qwen/Qwen2-7B
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
trust_remote_code: true
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: PocketDoc/Dans-MemoryCore-CoreCurriculum-Small
type: sharegpt
conversation: chatml
- path: NewEden/kaloisazasedhandsomefurry
type: sharegpt
conversation: chatml
- path: anthracite-org/kalo_opus_misc_240827
type: sharegpt
conversation: chatml
type: sharegpt
conversation: chatml
- path: AquaV/Chemical-Biological-Safety-Applications-Sharegpt
type: sharegpt
conversation: chatml
- path: AquaV/Energetic-Materials-Sharegpt
type: sharegpt
conversation: chatml
- path: lodrick-the-lafted/NopmWritingStruct
type: sharegpt
conversation: chatml
- path: NewEden/Claude-Instruct-5k
type: sharegpt
conversation: chatml
- path: lodrick-the-lafted/kalo-opus-instruct-3k-filtered
type: sharegpt
conversation: chatml
- path: anthracite-org/kalo-opus-instruct-22k-no-refusal
type: sharegpt
conversation: chatml
- path: NewEden/Stheno-Data-filtered-8k-subset
type: sharegpt
conversation: chatml
- path: Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
type: sharegpt
conversation: chatml
- path: PJMixers/lodrick-the-lafted_OpusStories-ShareGPT
type: sharegpt
conversation: chatml
chat_template: chatml
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./outputs/out
#sequence_len: 16384
sequence_len: 8192
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: henbane 7b
wandb_entity:
wandb_watch:
wandb_name: henbane 7b
wandb_log_model:
plugins:
- axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_swiglu: true
liger_fused_linear_cross_entropy: true
gradient_accumulation_steps: 32
micro_batch_size: 1
num_epochs: 2
optimizer: adamw_torch
lr_scheduler: cosine
learning_rate: 0.00002
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_steps: 10
evals_per_epoch: 4
saves_per_epoch: 1
debug:
weight_decay: 0.5
special_tokens:
deepspeed: /workspace/axolotl/deepspeed_configs/zero2.json
```
</details><br>
# outputs/out
This model is a fine-tuned version of [Qwen/Qwen2-7B](https://huggingface.co/Qwen/Qwen2-7B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0715
## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 32
- total_train_batch_size: 64
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.4364 | 0.0078 | 1 | 1.4088 |
| 1.1643 | 0.2499 | 32 | 1.1562 |
| 1.1112 | 0.4999 | 64 | 1.1158 |
| 1.0908 | 0.7498 | 96 | 1.0920 |
| 1.0575 | 0.9998 | 128 | 1.0752 |
| 0.8988 | 1.2331 | 160 | 1.0832 |
| 0.8887 | 1.4830 | 192 | 1.0752 |
| 0.8821 | 1.7330 | 224 | 1.0722 |
| 0.8939 | 1.9829 | 256 | 1.0715 |
### Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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