Training in progress, epoch 1

README.md

@@ -8,11 +8,6 @@ metrics:
 model-index:
 - name: sft-bge-bert24m-to-sentiment
   results: []
-pipeline_tag: text-classification
-datasets:
-- tyqiangz/multilingual-sentiments
-widget:
-- text: "王女士最近和老板吵了一架，似乎心情很沮丧。"
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -20,24 +15,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 # sft-bge-bert24m-to-sentiment
 
-This model is a fine-tuned version of [BAAI/bge-small-zh-v1.5](https://huggingface.co/BAAI/bge-small-zh-v1.5) on a dataset [tyqiangz/multilingual-sentiment](https://huggingface.co/tyqiangz/multilingual-sentiment)(name = 'chinese').
+This model is a fine-tuned version of [BAAI/bge-small-zh-v1.5](https://huggingface.co/BAAI/bge-small-zh-v1.5) on an unknown dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.5434
 - Accuracy: 0.779
 
-## Usage for the Model
-```
-# Use a pipeline as a high-level helper
-from transformers import pipeline
-
-pipe = pipeline("text-classification", model="dumyy/sft-bge-bert24m-to-sentiment")
-
-result = pipe("我最近遇到了很糟糕的事，让我异常郁闷。")
-
-print(result)
-```
-
-
 ## Model description
 
 More information needed
@@ -76,4 +58,4 @@ The following hyperparameters were used during training:
 - Transformers 4.37.2
 - Pytorch 2.2.0+cu121
 - Datasets 2.17.1
-- Tokenizers 0.15.2
+- Tokenizers 0.15.2

model.safetensors

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training_args.bin

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