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  1. README.md +16 -13
  2. adapter_config.json +4 -4
  3. adapter_model.bin +1 -1
  4. tokenizer_config.json +0 -1
README.md CHANGED
@@ -29,8 +29,17 @@ model_type: MistralForCausalLM
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  tokenizer_type: LlamaTokenizer
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  is_mistral_derived_model: true
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  # accelerate launch -m axolotl.cli.train ./llama_7b_config.yaml
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  load_in_8bit: true
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  load_in_4bit: false
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  strict: false
@@ -49,9 +58,6 @@ dataset_prepared_path:
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  val_set_size: 0.05
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  output_dir: ./lora-out
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- chat_template: chatml
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- default_system_message: You are a helpful assistant, specialising in financial text sentiment and emotional analysis. # Currently only supports chatml.
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-
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  sequence_len: 512
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  sample_packing: true
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  pad_to_sequence_len: true
@@ -71,7 +77,7 @@ wandb_name:
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  wandb_log_model:
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  gradient_accumulation_steps: 1
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- micro_batch_size: 16
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  # max_steps: 1000
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  num_epochs: 2
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  optimizer: adamw_bnb_8bit
@@ -94,7 +100,7 @@ flash_attention: true
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  s2_attention:
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  warmup_steps: 50
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- evals_per_epoch: 2
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  eval_table_size:
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  eval_table_max_new_tokens: 128
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  saves_per_epoch: 1
@@ -115,7 +121,7 @@ special_tokens:
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  This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0942
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  ## Model description
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@@ -135,8 +141,8 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0002
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- - train_batch_size: 16
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- - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
@@ -147,11 +153,8 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 3.8894 | 0.0 | 1 | 3.9316 |
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- | 0.1106 | 0.5 | 247 | 0.1150 |
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- | 0.0956 | 1.0 | 494 | 0.0998 |
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- | 0.0705 | 1.48 | 741 | 0.0990 |
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- | 0.0858 | 1.98 | 988 | 0.0942 |
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  ### Framework versions
 
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  tokenizer_type: LlamaTokenizer
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  is_mistral_derived_model: true
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+ # git clone https://github.com/OpenAccess-AI-Collective/axolotl
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+ # cd axolotl
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+
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+ # pip3 install packaging
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+ # pip3 install -e '.[flash-attn,deepspeed]'
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+
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  # accelerate launch -m axolotl.cli.train ./llama_7b_config.yaml
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+ # accelerate launch -m axolotl.cli.inference ./llama_7b_config.yaml \
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+ # --lora_model_dir="dohonba/mistral_7b_fingpt"
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+
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  load_in_8bit: true
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  load_in_4bit: false
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  strict: false
 
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  val_set_size: 0.05
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  output_dir: ./lora-out
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  sequence_len: 512
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  sample_packing: true
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  pad_to_sequence_len: true
 
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  wandb_log_model:
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  gradient_accumulation_steps: 1
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+ micro_batch_size: 14
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  # max_steps: 1000
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  num_epochs: 2
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  optimizer: adamw_bnb_8bit
 
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  s2_attention:
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  warmup_steps: 50
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+ evals_per_epoch: 0
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  eval_table_size:
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  eval_table_max_new_tokens: 128
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  saves_per_epoch: 1
 
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  This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0917
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0002
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+ - train_batch_size: 14
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+ - eval_batch_size: 14
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
 
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.08 | 1.02 | 566 | 0.0986 |
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+ | 0.0919 | 1.98 | 1110 | 0.0917 |
 
 
 
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  ### Framework versions
adapter_config.json CHANGED
@@ -19,13 +19,13 @@
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  "rank_pattern": {},
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  "revision": null,
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  "target_modules": [
 
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  "up_proj",
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- "q_proj",
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  "down_proj",
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- "v_proj",
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- "o_proj",
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  "gate_proj",
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- "k_proj"
 
 
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  ],
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  "task_type": "CAUSAL_LM"
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  }
 
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  "rank_pattern": {},
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  "revision": null,
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  "target_modules": [
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+ "v_proj",
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  "up_proj",
 
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  "down_proj",
 
 
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  "gate_proj",
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+ "k_proj",
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+ "o_proj",
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+ "q_proj"
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  ],
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  "task_type": "CAUSAL_LM"
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  }
adapter_model.bin CHANGED
@@ -1,3 +1,3 @@
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- oid sha256:fc7b054e6913ab8281151c4ba3ee1016c6930c443a8ea9aae2f778ae60f47ea9
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  size 335705741
 
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+ oid sha256:ed44fe38ab406e5b8a358047c9754533cfe79a547f5ae7d159b73dc5b5ba2319
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  size 335705741
tokenizer_config.json CHANGED
@@ -29,7 +29,6 @@
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  },
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  "additional_special_tokens": [],
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  "bos_token": "<s>",
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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, specialising in financial text sentiment and emotional analysis.' %}{% 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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  "clean_up_tokenization_spaces": false,
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  "eos_token": "</s>",
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  "legacy": true,
 
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  },
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  "additional_special_tokens": [],
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  "bos_token": "<s>",
 
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  "clean_up_tokenization_spaces": false,
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  "eos_token": "</s>",
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  "legacy": true,