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stablelm-3b-finance

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  1. README.md +215 -2
  2. config.json +2 -1
  3. model.safetensors +1 -1
  4. training_args.bin +2 -2
README.md CHANGED
@@ -5,9 +5,24 @@ tags:
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  - generated_from_trainer
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  datasets:
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  - financial_phrasebank
 
 
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  model-index:
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  - name: stablelm-3b-finance
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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
@@ -16,6 +31,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # stablelm-3b-finance
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  This model is a fine-tuned version of [stabilityai/stablelm-base-alpha-3b](https://huggingface.co/stabilityai/stablelm-base-alpha-3b) on the financial_phrasebank dataset.
 
 
 
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  ## Model description
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@@ -44,11 +62,206 @@ The following hyperparameters were used during training:
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  ### Training results
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  ### Framework versions
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- - Transformers 4.31.0
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  - Pytorch 2.0.1+cu117
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  - Datasets 2.14.4
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  - Tokenizers 0.13.3
 
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  - generated_from_trainer
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  datasets:
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  - financial_phrasebank
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+ metrics:
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+ - accuracy
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  model-index:
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  - name: stablelm-3b-finance
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: financial_phrasebank
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+ type: financial_phrasebank
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+ config: sentences_50agree
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+ split: train
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+ args: sentences_50agree
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.4080578512396694
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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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  # stablelm-3b-finance
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  This model is a fine-tuned version of [stabilityai/stablelm-base-alpha-3b](https://huggingface.co/stabilityai/stablelm-base-alpha-3b) on the financial_phrasebank dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 4.2656
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+ - Accuracy: 0.4081
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 37.5127 | 0.01 | 20 | 19.6094 | 0.2624 |
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+ | 19.1885 | 0.01 | 40 | 64.3125 | 0.0816 |
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+ | 14.5964 | 0.02 | 60 | 43.4688 | 0.4143 |
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+ | 5.8184 | 0.02 | 80 | 54.9688 | 0.4143 |
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+ | 25.0629 | 0.03 | 100 | 62.25 | 0.0816 |
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+ | 23.0213 | 0.03 | 120 | 18.4062 | 0.4143 |
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+ | 6.4438 | 0.04 | 140 | 9.4922 | 0.4143 |
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+ | 10.3302 | 0.04 | 160 | 25.0781 | 0.4143 |
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+ | 5.5922 | 0.05 | 180 | 29.0469 | 0.4143 |
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+ | 2.9618 | 0.05 | 200 | 14.5078 | 0.4143 |
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+ | 4.551 | 0.06 | 220 | 18.5156 | 0.4112 |
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+ | 4.5168 | 0.06 | 240 | 29.5156 | 0.4143 |
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+ | 3.0656 | 0.07 | 260 | 27.5469 | 0.4143 |
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+ | 6.9075 | 0.07 | 280 | 40.375 | 0.4143 |
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+ | 6.09 | 0.08 | 300 | 28.4688 | 0.4143 |
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+ | 2.254 | 0.08 | 320 | 35.375 | 0.4143 |
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+ | 8.4998 | 0.09 | 340 | 31.4375 | 0.4143 |
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+ | 8.3815 | 0.09 | 360 | 28.2188 | 0.4143 |
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+ | 7.9155 | 0.1 | 380 | 12.0625 | 0.0816 |
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+ | 2.0166 | 0.1 | 400 | 9.8672 | 0.3895 |
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+ | 5.1889 | 0.11 | 420 | 11.0234 | 0.4132 |
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+ | 3.844 | 0.11 | 440 | 10.4844 | 0.4132 |
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+ | 3.7982 | 0.12 | 460 | 13.4688 | 0.3864 |
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+ | 1.5386 | 0.12 | 480 | 34.3125 | 0.4143 |
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+ | 4.0882 | 0.13 | 500 | 33.875 | 0.4143 |
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+ | 6.1486 | 0.13 | 520 | 11.6406 | 0.0816 |
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+ | 4.0523 | 0.14 | 540 | 9.1328 | 0.3988 |
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+ | 2.5312 | 0.14 | 560 | 11.7969 | 0.4143 |
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+ | 6.0803 | 0.15 | 580 | 15.6016 | 0.4143 |
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+ | 5.4927 | 0.15 | 600 | 8.8828 | 0.0816 |
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+ | 4.4524 | 0.17 | 660 | 6.5312 | 0.4122 |
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+ | 6.081 | 0.18 | 680 | 34.3125 | 0.4112 |
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+ | 7.9303 | 0.18 | 700 | 45.9375 | 0.0868 |
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112
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+ | 3.595 | 0.28 | 1080 | 13.2422 | 0.4143 |
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+ | 2.0884 | 0.99 | 3840 | 4.2656 | 0.4081 |
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+ | 2.1517 | 1.0 | 3860 | 4.2656 | 0.4081 |
260
 
261
 
262
  ### Framework versions
263
 
264
+ - Transformers 4.32.0
265
  - Pytorch 2.0.1+cu117
266
  - Datasets 2.14.4
267
  - Tokenizers 0.13.3
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@@ -29,12 +29,13 @@
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  "vocab_size": 50688
 
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  "pad_token_id": 0,
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  "pretraining_tp": 1,
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+ "problem_type": "single_label_classification",
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