---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.3
tags:
- axolotl
- generated_from_trainer
model-index:
- name: Mistral-7B-v0.3-sarcasm-scrolls-v2
  results: []
datasets:
- BEE-spoke-data/sarcasm-scrolls
language:
- en
---

<!-- 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: `0.4.1`
```yaml
base_model: mistralai/Mistral-7B-v0.3
model_type: MistralForCausalLM
tokenizer_type: LlamaTokenizer

strict: false

# dataset
datasets:
    - path: BEE-spoke-data/sarcasm-scrolls
      type: completion # format from earlier
      field: text
val_set_size: 200

sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true
train_on_inputs: false
group_by_length: false

# WANDB
wandb_project: sarcasm-scrolls
wandb_entity: pszemraj
wandb_watch: gradients
wandb_name: Mistral-7B-v0.3-sarcasm-scrolls-v2a
hub_model_id: pszemraj/Mistral-7B-v0.3-sarcasm-scrolls-v2
hub_strategy: every_save

gradient_accumulation_steps: 32
micro_batch_size: 1
num_epochs: 2
optimizer: adamw_torch_fused # paged_adamw_32bit
lr_scheduler: cosine
learning_rate: 2e-5

load_in_8bit: false
load_in_4bit: false
bf16: true
tf32: true

torch_compile: true 
torch_compile_backend: inductor # Optional[str]
gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: false
early_stopping_patience:
logging_steps: 3
xformers_attention:
flash_attention: true

warmup_steps: 20
# hyperparams for freq of evals, saving, etc
evals_per_epoch: 4
saves_per_epoch: 4
save_safetensors: true
save_total_limit: 1 # Checkpoints saved at a time
output_dir: ./output-axolotl/output-model-chaz
resume_from_checkpoint:


deepspeed:
weight_decay: 0.06

special_tokens:

```

</details><br>

# Mistral-7B-v0.3-sarcasm-scrolls-v2

## Model description

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3) on the BEE-spoke-data/sarcasm-scrolls dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3333


## 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
- gradient_accumulation_steps: 32
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 20
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0075 | 1    | 2.3935          |
| 2.3672        | 0.2548 | 34   | 2.3638          |
| 2.3751        | 0.5096 | 68   | 2.3499          |
| 2.308         | 0.7644 | 102  | 2.3238          |
| 2.2672        | 1.0035 | 136  | 2.3027          |
| 1.702         | 1.2583 | 170  | 2.3449          |
| 1.7456        | 1.5131 | 204  | 2.3370          |
| 1.7004        | 1.7679 | 238  | 2.3333          |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.1+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1