---
library_name: transformers
base_model: Dans-DiscountModels/mistral-7b-v0.3-ChatML
tags:
- axolotl
- generated_from_trainer
datasets:
- Dans-DiscountModels/pretokenization-test-2
model-index:
- name: 7b-m-dans-personalityengine-v1.2.1-rc-5
  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: `0.8.0`
```yaml
base_model: Dans-DiscountModels/mistral-7b-v0.3-ChatML
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

trust_remote_code:

# wandb configuration
wandb_project: 7b-m-dans-personalityengine
wandb_watch:

wandb_run_id: V1.2.1-4-1 # V{Version}-{Run Number}-{Attempt Number}
wandb_log_model:

# push checkpoints to hub
hub_model_id: Dans-DiscountModels/7b-m-dans-personalityengine-v1.2.1-rc-5
# how to push checkpoints to hub
# https://huggingface.co/docs/transformers/v4.31.0/en/main_classes/trainer#transformers.TrainingArguments.hub_strategy
hub_strategy: "every_save"
# Whether to use hf `use_auth_token` for loading datasets. Useful for fetching private datasets
# Required to be true when used in combination with `push_dataset_to_hub`
hf_use_auth_token: true

# where to save the finished model to
output_dir: ./7b-m-dans-personalityengine

# where to save the dataset to
dataset_prepared_path: ./7b-m-dans-personalityengine-data

save_safetensors: true

# dataset settings (local or huggingface repo)
datasets:
  - path: Dans-DiscountModels/pretokenization-test-2
    ds_type: parquet
    type:

plugins:
  - axolotl.integrations.liger.LigerPlugin
  - axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
liger_fused_linear_cross_entropy: false
cut_cross_entropy: true

load_in_8bit: false
load_in_4bit: false
strict: false

val_set_size: 0.005
sequence_len: 32768

sample_packing: true
eval_sample_packing: true

pad_to_sequence_len: true

gradient_checkpointing: true
# gradient_checkpointing_kwargs:
# use_reentrant: false

gradient_accumulation_steps: 2
micro_batch_size: 2

num_epochs: 1

optimizer: ademamix_8bit
optim_args: "beta1=0.9,beta2=0.999,beta3=0.999,alpha=10"

lr_scheduler: rex
learning_rate: 0.00000015
cosine_min_lr_ratio: 0.1

# weight_decay: 0.03
max_grad_norm: 0.001

train_on_inputs: false
group_by_length: false

bf16: true
fp16: false
tf32: false

early_stopping_patience:

resume_from_checkpoint:
auto_resume_from_checkpoints: false

local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_ratio: 0.03

evals_per_epoch: 24
eval_table_size:
eval_max_new_tokens:

saves_per_epoch: 2
save_total_limit: 1

debug: false

deepspeed: deepspeed_configs/zero3_bf16.json

fsdp:
fsdp_config:

special_tokens:

```

</details><br>

# 7b-m-dans-personalityengine-v1.2.1-rc-5

This model is a fine-tuned version of [Dans-DiscountModels/mistral-7b-v0.3-ChatML](https://huggingface.co/Dans-DiscountModels/mistral-7b-v0.3-ChatML) on the Dans-DiscountModels/pretokenization-test-2 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4047

## 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: 1.5e-07
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Use ademamix_8bit and the args are:
beta1=0.9,beta2=0.999,beta3=0.999,alpha=10
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 43
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.5957        | 0.0007 | 1    | 1.5418          |
| 1.487         | 0.0417 | 61   | 1.4982          |
| 1.5851        | 0.0833 | 122  | 1.4720          |
| 1.3702        | 0.125  | 183  | 1.4596          |
| 1.5285        | 0.1667 | 244  | 1.4519          |
| 1.4809        | 0.2083 | 305  | 1.4461          |
| 1.3806        | 0.25   | 366  | 1.4414          |
| 1.5097        | 0.2917 | 427  | 1.4373          |
| 1.497         | 0.3333 | 488  | 1.4338          |
| 1.503         | 0.375  | 549  | 1.4306          |
| 1.384         | 0.4167 | 610  | 1.4278          |
| 1.4191        | 0.4583 | 671  | 1.4252          |
| 1.3042        | 0.5    | 732  | 1.4228          |
| 1.5669        | 0.5417 | 793  | 1.4206          |
| 1.4239        | 0.5833 | 854  | 1.4185          |
| 1.4472        | 0.625  | 915  | 1.4165          |
| 1.4692        | 0.6667 | 976  | 1.4147          |
| 1.4358        | 0.7083 | 1037 | 1.4130          |
| 1.4676        | 0.75   | 1098 | 1.4114          |
| 1.4657        | 0.7917 | 1159 | 1.4099          |
| 1.424         | 0.8333 | 1220 | 1.4085          |
| 1.3385        | 0.875  | 1281 | 1.4072          |
| 1.4373        | 0.9167 | 1342 | 1.4061          |
| 1.4226        | 0.9583 | 1403 | 1.4052          |
| 1.4225        | 1.0    | 1464 | 1.4047          |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1