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prem-1B-chat-32k

PEFT
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Safetensors
llama
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prem-1B-chat-32k
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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: premai-io/prem-1B-chat
model-index:
- name: prem-1B-chat-32k
  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: premai-io/prem-1B-chat
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
load_in_4bit: false
strict: false

datasets:
  - path: argilla/distilabel-capybara-dpo-7k-binarized
    type: orpo.chat_template
dataset_prepared_path: last_run_prepared
val_set_size: 0.001
output_dir: ./prem-1B-chat-32k
save_safetensors: true
sequence_len: 8192
sample_packing: false
pad_to_sequence_len: false
use_pose: true
pose_max_context_len: 262144
min_sample_len: 6144
pose_num_chunks: 16
curriculum_sampling: true

overrides_of_model_config:
  rope_theta: 500000.0
  max_position_embeddings: 262144

  # peft_use_dora: true
adapter: lora
peft_use_rslora: true
lora_model_dir:
lora_r: 1024
lora_alpha: 1024
lora_dropout: 0.1
lora_target_modules:
  - q_proj
  - k_proj
  - v_proj
  - o_proj
lora_modules_to_save:
  - embed_tokens
  - lm_head

wandb_project:
wandb_entity: 
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 8
micro_batch_size: 1
num_epochs: 20
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.00001
max_grad_norm: 1.0
adam_beta2: 0.95

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

gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
sdp_attention:
s2_attention:

warmup_steps: 10
evals_per_epoch: 8
saves_per_epoch: 8
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  pad_token: <|end_of_text|>



```

</details><br>

# prem-1B-chat-32k

This model is a fine-tuned version of [premai-io/prem-1B-chat](https://huggingface.co/premai-io/prem-1B-chat) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 6.9843

## 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-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5389        | 1.0   | 1    | 6.3469          |
| 0.5389        | 2.0   | 2    | 6.2533          |
| 0.5017        | 3.0   | 3    | 6.2101          |
| 0.4689        | 4.0   | 4    | 6.3163          |
| 0.3604        | 5.0   | 5    | 6.4144          |
| 0.3107        | 6.0   | 6    | 6.4127          |
| 0.2698        | 7.0   | 7    | 6.8089          |
| 0.317         | 8.0   | 8    | 7.3388          |
| 0.2228        | 9.0   | 9    | 6.5063          |
| 0.1798        | 10.0  | 10   | 5.7073          |
| 0.1436        | 11.0  | 11   | 5.1185          |
| 0.1183        | 12.0  | 12   | 4.8994          |
| 0.1002        | 13.0  | 13   | 4.8033          |
| 0.0865        | 14.0  | 14   | 5.1707          |
| 0.0758        | 15.0  | 15   | 5.7089          |
| 0.0663        | 16.0  | 16   | 6.4052          |
| 0.0601        | 17.0  | 17   | 6.7814          |
| 0.0545        | 18.0  | 18   | 6.9586          |
| 0.0505        | 19.0  | 19   | 6.9766          |
| 0.0482        | 20.0  | 20   | 6.9843          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0