End of training
Browse files- README.md +14 -2
- all_results.json +15 -0
- eval_results.json +10 -0
- train_results.json +8 -0
- trainer_state.json +508 -0
README.md
CHANGED
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@@ -3,11 +3,23 @@ license: llama2
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base_model: meta-llama/Llama-2-7b-hf
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: lmind_hotpot_train8000_eval7405_v1_qa_3e-5_lora2
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-
results:
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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@@ -15,7 +27,7 @@ should probably proofread and complete it, then remove this comment. -->
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# lmind_hotpot_train8000_eval7405_v1_qa_3e-5_lora2
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-
This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on
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It achieves the following results on the evaluation set:
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- Loss: 2.9797
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- Accuracy: 0.5824
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base_model: meta-llama/Llama-2-7b-hf
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tags:
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- generated_from_trainer
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+
datasets:
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+
- tyzhu/lmind_hotpot_train8000_eval7405_v1_qa
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metrics:
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- accuracy
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model-index:
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- name: lmind_hotpot_train8000_eval7405_v1_qa_3e-5_lora2
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+
results:
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+
- task:
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name: Causal Language Modeling
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type: text-generation
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dataset:
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name: tyzhu/lmind_hotpot_train8000_eval7405_v1_qa
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type: tyzhu/lmind_hotpot_train8000_eval7405_v1_qa
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.5824050632911393
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---
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| 24 |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# lmind_hotpot_train8000_eval7405_v1_qa_3e-5_lora2
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+
This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the tyzhu/lmind_hotpot_train8000_eval7405_v1_qa dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.9797
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- Accuracy: 0.5824
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all_results.json
ADDED
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@@ -0,0 +1,15 @@
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{
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"epoch": 20.0,
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"eval_accuracy": 0.5824050632911393,
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+
"eval_loss": 2.9796953201293945,
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+
"eval_runtime": 4.8607,
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+
"eval_samples": 500,
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+
"eval_samples_per_second": 102.866,
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+
"eval_steps_per_second": 12.961,
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"perplexity": 19.681819077050044,
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+
"train_loss": 1.043557526397705,
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+
"train_runtime": 3605.2187,
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+
"train_samples": 8000,
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"train_samples_per_second": 44.38,
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"train_steps_per_second": 1.387
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}
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eval_results.json
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{
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"epoch": 20.0,
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"eval_accuracy": 0.5824050632911393,
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+
"eval_loss": 2.9796953201293945,
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"eval_runtime": 4.8607,
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"eval_samples": 500,
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"eval_samples_per_second": 102.866,
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"eval_steps_per_second": 12.961,
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"perplexity": 19.681819077050044
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}
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train_results.json
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{
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"epoch": 20.0,
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"train_loss": 1.043557526397705,
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"train_runtime": 3605.2187,
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"train_samples": 8000,
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"train_samples_per_second": 44.38,
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"train_steps_per_second": 1.387
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}
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trainer_state.json
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@@ -0,0 +1,508 @@
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|
| 1 |
+
{
|
| 2 |
+
"best_metric": null,
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| 3 |
+
"best_model_checkpoint": null,
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| 4 |
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"epoch": 20.0,
|
| 5 |
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"eval_steps": 500,
|
| 6 |
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"global_step": 5000,
|
| 7 |
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"is_hyper_param_search": false,
|
| 8 |
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"is_local_process_zero": true,
|
| 9 |
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"is_world_process_zero": true,
|
| 10 |
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"log_history": [
|
| 11 |
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{
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| 12 |
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"epoch": 0.4,
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| 13 |
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"learning_rate": 3e-05,
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| 14 |
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"loss": 2.3698,
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| 15 |
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"step": 100
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},
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| 17 |
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{
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| 18 |
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"epoch": 0.8,
|
| 19 |
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"learning_rate": 3e-05,
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| 20 |
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"loss": 1.8255,
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| 21 |
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"step": 200
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| 22 |
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},
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| 23 |
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{
|
| 24 |
+
"epoch": 1.0,
|
| 25 |
+
"eval_accuracy": 0.6054430379746836,
|
| 26 |
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"eval_loss": 1.83919358253479,
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| 27 |
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"eval_runtime": 4.6476,
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| 28 |
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"eval_samples_per_second": 107.584,
|
| 29 |
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"eval_steps_per_second": 13.556,
|
| 30 |
+
"step": 250
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| 31 |
+
},
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| 32 |
+
{
|
| 33 |
+
"epoch": 1.2,
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| 34 |
+
"learning_rate": 3e-05,
|
| 35 |
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"loss": 1.7843,
|
| 36 |
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"step": 300
|
| 37 |
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},
|
| 38 |
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{
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| 39 |
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"epoch": 1.6,
|
| 40 |
+
"learning_rate": 3e-05,
|
| 41 |
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"loss": 1.7546,
|
| 42 |
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"step": 400
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| 43 |
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},
|
| 44 |
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{
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| 45 |
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"epoch": 2.0,
|
| 46 |
+
"learning_rate": 3e-05,
|
| 47 |
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"loss": 1.7368,
|
| 48 |
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"step": 500
|
| 49 |
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},
|
| 50 |
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{
|
| 51 |
+
"epoch": 2.0,
|
| 52 |
+
"eval_accuracy": 0.6078227848101266,
|
| 53 |
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"eval_loss": 1.81111478805542,
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| 54 |
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"eval_runtime": 4.7063,
|
| 55 |
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"eval_samples_per_second": 106.242,
|
| 56 |
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