Quant for 5.0

README.md

@@ -7,63 +7,169 @@ tags:
 model-index:
 - name: Einstein-v4-7B
   results: []
-quantized_by: bartowski
-pipeline_tag: text-generation
 ---
 
-## Exllama v2 Quantizations of Einstein-v4-7B
+<!-- 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. -->
 
-Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.14">turboderp's ExLlamaV2 v0.0.14</a> for quantization.
+[<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>
 
-<b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b>
+axolotl version: `0.4.0`
+```yaml
+base_model: mistralai/Mistral-7B-v0.1
+model_type: MistralForCausalLM
+tokenizer_type: LlamaTokenizer
+is_mistral_derived_model: true
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+chat_template: chatml
+datasets:
+  - path: data/merged_all.json
+    ds_type: json
+    type: alpaca
+    conversation: chatml
+
+  - path: data/capybara_sharegpt.json
+    ds_type: json
+    type: sharegpt
+    conversation: chatml
+
+  - path: data/synthia-v1.3_sharegpt_12500.json
+    ds_type: json
+    type: sharegpt
+    conversation: chatml  
+
+  - path: data/cot_alpaca_gpt4_extracted_openhermes_2.5_sharegpt.json
+    ds_type: json
+    type: sharegpt
+    conversation: chatml
+
+  - path: data/slimorca_dedup_filtered_95k_sharegpt.json
+    ds_type: json
+    type: sharegpt
+    conversation: chatml  
+
+  - path: data/airoboros_3.2_without_contextual_slimorca_orca_sharegpt.json
+    ds_type: json
+    type: sharegpt
+    conversation: chatml  
+
+dataset_prepared_path: last_run_prepared
+val_set_size: 0.005
+output_dir: ./Einstein-v4-model
+
+sequence_len: 8192
+sample_packing: true
+pad_to_sequence_len: true
+eval_sample_packing: false
+
+wandb_project: Einstein
+wandb_entity:
+wandb_watch:
+wandb_name:
+wandb_log_model:
+hub_model_id: Weyaxi/Einstein-v4-7B
+
+save_safetensors: true
+
+gradient_accumulation_steps: 4
+micro_batch_size: 1
+num_epochs: 1.5
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 0.000005
+
+train_on_inputs: false
+group_by_length: false
+bf16: true
+fp16: false
+tf32: false
+
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+warmup_steps: 10
+evals_per_epoch: 2 # changed
+eval_table_size:
+eval_table_max_new_tokens: 128
+saves_per_epoch: 4
+debug:
+
+deepspeed: zero3_bf16.json
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+  bos_token: "<s>"
+  eos_token: "<|im_end|>"
+  unk_token: "<unk>"
+tokens:
+  - "<|im_start|>"
+
+resume_from_checkpoint: Einstein-v4-model/checkpoint-521
 
-Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.
+```
 
-Original model: https://huggingface.co/Weyaxi/Einstein-v4-7B
+</details><br>
 
-| Branch | Bits | lm_head bits | VRAM (4k) | VRAM (16k) | VRAM (32k) | Description |
-| ----- | ---- | ------- | ------ | ------ | ------ | ------------ |
-| [8_0](https://huggingface.co/bartowski/Einstein-v4-7B-exl2/tree/8_0) | 8.0 | 8.0 | 8.4 GB | 9.8 GB | 11.8 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. |
-| [6_5](https://huggingface.co/bartowski/Einstein-v4-7B-exl2/tree/6_5) | 6.5 | 8.0 | 7.2 GB | 8.6 GB | 10.6 GB | Very similar to 8.0, good tradeoff of size vs performance, **recommended**. |
-| [5_0](https://huggingface.co/bartowski/Einstein-v4-7B-exl2/tree/5_0) | 5.0 | 6.0 | 6.0 GB | 7.4 GB |  9.4 GB | Slightly lower quality vs 6.5, but usable on 8GB cards. |
-| [4_25](https://huggingface.co/bartowski/Einstein-v4-7B-exl2/tree/4_25) | 4.25 | 6.0 | 5.3 GB | 6.7 GB | 8.7 GB | GPTQ equivalent bits per weight, slightly higher quality. |
-| [3_5](https://huggingface.co/bartowski/Einstein-v4-7B-exl2/tree/3_5) | 3.5 | 6.0 | 4.7 GB | 6.1 GB | 8.1 GB | Lower quality, only use if you have to. |
+# Einstein-v4-7B
 
-## Download instructions
+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.
+It achieves the following results on the evaluation set:
+- Loss: 0.4902
 
-With git:
+## Model description
 
-```shell
-git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/Einstein-v4-7B-exl2 Einstein-v4-7B-exl2-6_5
-```
+More information needed
 
-With huggingface hub (credit to TheBloke for instructions):
+## Intended uses & limitations
 
-```shell
-pip3 install huggingface-hub
-```
+More information needed
 
-To download the `main` (only useful if you only care about measurement.json) branch to a folder called `Einstein-v4-7B-exl2`:
+## Training and evaluation data
 
-```shell
-mkdir Einstein-v4-7B-exl2
-huggingface-cli download bartowski/Einstein-v4-7B-exl2 --local-dir Einstein-v4-7B-exl2 --local-dir-use-symlinks False
-```
+More information needed
 
-To download from a different branch, add the `--revision` parameter:
+## Training procedure
 
-Linux:
+### Training hyperparameters
 
-```shell
-mkdir Einstein-v4-7B-exl2-6_5
-huggingface-cli download bartowski/Einstein-v4-7B-exl2 --revision 6_5 --local-dir Einstein-v4-7B-exl2-6_5 --local-dir-use-symlinks False
-```
+The following hyperparameters were used during training:
+- learning_rate: 5e-06
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- total_eval_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: 1.5
 
-Windows (which apparently doesn't like _ in folders sometimes?):
+### Training results
 
-```shell
-mkdir Einstein-v4-7B-exl2-6.5
-huggingface-cli download bartowski/Einstein-v4-7B-exl2 --revision 6_5 --local-dir Einstein-v4-7B-exl2-6.5 --local-dir-use-symlinks False
-```
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 1.1358        | 0.0   | 1    | 1.2075          |
+| 0.5083        | 0.5   | 521  | 0.5161          |
+| 0.4759        | 1.0   | 1042 | 0.4902          |
+
+
+### Framework versions
 
-Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski
+- Transformers 4.38.0.dev0
+- Pytorch 2.1.2+cu118
+- Datasets 2.16.1
+- Tokenizers 0.15.0

added_tokens.json

@@ -0,0 +1,4 @@
+{
+  "<|im_end|>": 32000,
+  "<|im_start|>": 32001
+}

config.json

@@ -0,0 +1,26 @@
+{
+  "_name_or_path": "mistralai/Mistral-7B-v0.1",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 32000,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.38.0.dev0",
+  "use_cache": false,
+  "vocab_size": 32002
+}

generation_config.json

@@ -0,0 +1,7 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "do_sample": true,
+  "eos_token_id": 2,
+  "transformers_version": "4.38.0.dev0"
+}

model.safetensors.index.json

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