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README.md

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+---
+license: apache-2.0
+library_name: peft
+tags:
+- axolotl
+- generated_from_trainer
+base_model: mistralai/Mistral-7B-Instruct-v0.2
+model-index:
+- name: financial-phrasebank-sentiment-reasoning
+  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: mistralai/Mistral-7B-Instruct-v0.2
+model_type: MistralForCausalLM
+tokenizer_type: LlamaTokenizer
+
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+
+chat_template: chatml
+datasets:
+  - path: winglian/financial_phrasebank_augmented
+    type: sharegpt
+    split: train
+    strict: false
+test_datasets:
+  - path: winglian/financial_phrasebank_augmented-validation
+    type: sharegpt
+    split: train
+    strict: false
+dataset_prepared_path: last_run_prepared
+val_set_size: 0.0
+output_dir: ./finetuned-out
+hub_model_id: winglian/financial-phrasebank-sentiment-reasoning
+
+adapter: lora
+lora_model_dir:
+
+sequence_len: 768 
+sample_packing: false
+pad_to_sequence_len: false
+
+lora_r: 32
+lora_alpha: 16
+lora_dropout: 0.1
+lora_target_modules:
+  - gate_proj
+  - down_proj
+  - up_proj
+  - q_proj
+  - v_proj
+  - k_proj
+  - o_proj
+lora_modules_to_save:
+  - embed_tokens
+  - lm_head
+
+wandb_project: financial-phrasebank-reasoning
+wandb_entity: oaaic
+wandb_watch:
+wandb_name:
+wandb_log_model:
+
+gradient_accumulation_steps: 4
+micro_batch_size: 2
+num_epochs: 3
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 0.00001
+
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: true
+
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+loss_watchdog_threshold: 5.0
+loss_watchdog_patience: 3
+
+warmup_steps: 10
+evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+  eos_token: "<|im_end|>"
+tokens:
+  - "<|im_start|>"
+
+```
+
+</details><br>
+
+# financial-phrasebank-sentiment-reasoning
+
+This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6457
+
+## 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: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 10
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 1.1125        | 0.0   | 1    | 1.3634          |
+| 0.4981        | 0.25  | 71   | 0.7488          |
+| 0.3236        | 0.5   | 142  | 0.6989          |
+| 0.2667        | 0.76  | 213  | 0.6727          |
+| 0.2922        | 1.01  | 284  | 0.6553          |
+| 0.2897        | 1.26  | 355  | 0.6526          |
+| 0.3039        | 1.51  | 426  | 0.6491          |
+| 0.2948        | 1.77  | 497  | 0.6462          |
+| 0.2858        | 2.02  | 568  | 0.6440          |
+| 0.2795        | 2.27  | 639  | 0.6448          |
+| 0.1904        | 2.52  | 710  | 0.6463          |
+| 0.2829        | 2.77  | 781  | 0.6457          |
+
+
+### Framework versions
+
+- PEFT 0.9.1.dev0
+- Transformers 4.39.0.dev0
+- Pytorch 2.1.2+cu118
+- Datasets 2.18.0
+- Tokenizers 0.15.0

adapter/adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.2",
+  "bias": "none",
+  "fan_in_fan_out": null,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": [
+    "embed_tokens",
+    "lm_head"
+  ],
+  "peft_type": "LORA",
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "down_proj",
+    "v_proj",
+    "q_proj",
+    "gate_proj",
+    "k_proj",
+    "o_proj",
+    "up_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

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adapter/config.json

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+    "MistralForCausalLM"
+  ],
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+    "bnb_4bit_use_double_quant": false,
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+  "vocab_size": 32002
+}

added_tokens.json

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+{
+  "<|im_end|>": 32000,
+  "<|im_start|>": 32001
+}

config.json

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+{
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+  "architectures": [
+    "MistralForCausalLM"
+  ],
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+  "bos_token_id": 1,
+  "eos_token_id": 32000,
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+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.39.0.dev0",
+  "use_cache": false,
+  "vocab_size": 32002
+}

generation_config.json

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+  "bos_token_id": 1,
+  "do_sample": true,
+  "eos_token_id": 2,
+  "transformers_version": "4.39.0.dev0"
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special_tokens_map.json

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+{
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+    "normalized": false,
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+    "single_word": false
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+    "normalized": false,
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+}

tokenizer.model

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+oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
+size 493443

tokenizer_config.json

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+    "32000": {
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+      "single_word": false,
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+  "chat_template": "{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = 'You are a helpful assistant.' %}{% endif %}{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in loop_messages %}{% if loop.index0 == 0 %}{{'<|im_start|>system\n' + system_message + '<|im_end|>\n'}}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
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