---
license: apache-2.0
base_model: Alignment-Lab-AI/Alignment-Lab-AIlonger
tags:
- axolotl
- generated_from_trainer
model-index:
- name: Eros-BETA
  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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.4.0`
```yaml
base_model: Alignment-Lab-AI/Alignment-Lab-AIlonger
load_in_8bit: false
load_in_4bit: false
strict: false
tokenizer_type: LlamaTokenizer

datasets:
  - path: PygmalionAI/spice
    type: sharegpt
    conversation: chatml

  - path: PygmalionAI/NYROS
    type: sharegpt
    conversation: chatml

chat_template: chatml

dataset_prepared_path: /workspace/disk2/2prepath2
val_set_size: 0.05
output_dir: /workspace/disk2/Eros2-b
eval_sample_packing: true
sequence_len: 16384
sample_packing: true
pad_to_sequence_len: true
torch_compile: true
hf_use_auth_token: true
hub_strategy: all_checkpoints
hub_model_id: PygmalionAI/Eros-BETA
hub_private_repo: true
push_to_hub: true
wandb_project: Erosium-b
wandb_entity:
wandb_watch: all
overwrite_output_dir: true
wandb_name:
wandb_log_model:
save_safetensors: true
gradient_accumulation_steps: 4
micro_batch_size: 1
num_epochs: 4
optimizer: adamw_bnb_8bit
amsgrad: true
max_grad_norm: 1
lr_scheduler: 'cosine'
lr_scheduler_kwargs:
  num_cycles: 6
learning_rate: 0.00005
gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: false
train_on_inputs: false
group_by_length: true
neftune_noise_alpha: 6
bf16: auto
fp16:
tf32: false
seed: 314159
early_stopping_patience:
local_rank:
logging_steps: 1
log_level: debug
xformers_attention:
flash_attention: true
warmup_steps:
eval_per_epoch: 0.25
save_steps: 0.20
debug:
deepspeed: ./deepspeed_configs/zero2.json
weight_decay: 0.05
fsdp:
fsdp_config:
special_tokens:
  bos_token: "<s>"
  eos_token: "</s>"
  unk_token: "<unk>"
tokens:
  - "<|im_start|>"
  - "<|im_end|>"

```

</details><br>

# Eros-BETA

This model is a fine-tuned version of [Alignment-Lab-AI/Alignment-Lab-AIlonger](https://huggingface.co/Alignment-Lab-AI/Alignment-Lab-AIlonger) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1394

## 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: 1
- eval_batch_size: 1
- seed: 314159
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 3
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.267         | 1.02  | 224  | 1.3057          |
| 1.1657        | 2.02  | 448  | 1.2184          |
| 1.062         | 3.02  | 672  | 1.1664          |
| 0.8812        | 3.94  | 880  | 1.1394          |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.0