Model save

README.md

@@ -6,23 +6,18 @@ tags:
 datasets:
 - tweet_eval
 model-index:
-- name: results
+- name: MND_TweetEvalBert_model
   results: []
-language:
-- en
-metrics:
-- accuracy
-pipeline_tag: text-classification
 ---
 
 <!-- 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. -->
 
-# results
+# MND_TweetEvalBert_model
 
 This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the tweet_eval dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.2353
+- Loss: 0.7241
 
 ## Model description
 
@@ -30,7 +25,7 @@ More information needed
 
 ## Intended uses & limitations
 
-This model is used for sentimental analysis. It can identify 4 ranges of emotions only [Joy, Optimism, Anger, Sadness].
+More information needed
 
 ## Training and evaluation data
 
@@ -58,4 +53,4 @@ The following hyperparameters were used during training:
 - Transformers 4.32.0.dev0
 - Pytorch 2.0.1+cu118
 - Datasets 2.14.4
-- Tokenizers 0.13.3
+- Tokenizers 0.13.3

pytorch_model.bin

@@ -1,3 +1,3 @@
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+oid sha256:abc6a6ef6463b63e3ff95603985696cc83524d8eb39c35671981684da5501748
 size 438009649