End of training

README.md

@@ -7,23 +7,8 @@ metrics:
 - accuracy
 - f1
 model-index:
-- name: financial_twhin_bert_large_7labels
+- name: financial-twhin-bert-large-7labels
   results: []
-datasets:
-- FinGPT/fingpt-sentiment-train
-language:
-- en
-widget:
-- text: "$KTOS: Kratos Defense and Security awarded a $39 million sole-source contract for Geolocation Global Support Service"
-  example_title: "Example 1"
-- text: "$Google parent Alphabet Inc. reported revenue and earnings that fell short of analysts' expectations, showing the company's search advertising juggernaut was not immune to a slowdown in the digital ad market. The shares fell more than 6%."
-  example_title: "Example 2"
-- text: "$LJPC - La Jolla Pharma to reassess development of LJPC-401"
-  example_title: "Example 3"
-- text: "Watch $MARK over 43c in after-hours for continuation targeting the 50c area initially"
-  example title: "Example 4"
-- text: "$RCII: Rent-A-Center provides update - March revenues were off by about 5% versus last year"
-  example title: "Example 5"
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,11 +16,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 # financial-twhin-bert-large-7labels
 
-This model is a fine-tuned version of [Twitter/twhin-bert-large](https://huggingface.co/Twitter/twhin-bert-large) on 61K financial tweets.
+This model is a fine-tuned version of [Twitter/twhin-bert-large](https://huggingface.co/Twitter/twhin-bert-large) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7361
-- Accuracy: 0.8946
-- F1: 0.8969
+- Loss: 0.3040
+- Accuracy: 0.8968
+- F1: 0.8916
 
 ## Model description
 
@@ -54,21 +39,30 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 6.284712783126724e-06
-- train_batch_size: 8
+- learning_rate: 2.1732582582331977e-05
+- train_batch_size: 16
 - eval_batch_size: 8
-- seed: 42
+- seed: 1203
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 10
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 2
 
 ### Training results
 
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
+| 0.9592        | 0.3272 | 1500 | 0.6466          | 0.7665   | 0.7503 |
+| 0.4705        | 0.6545 | 3000 | 0.3785          | 0.8674   | 0.8528 |
+| 0.4196        | 0.9817 | 4500 | 0.5830          | 0.7892   | 0.7775 |
+| 0.3403        | 1.3089 | 6000 | 0.3683          | 0.8767   | 0.8728 |
+| 0.2962        | 1.6361 | 7500 | 0.3288          | 0.8889   | 0.8904 |
+| 0.272         | 1.9634 | 9000 | 0.3040          | 0.8968   | 0.8916 |
 
 
 ### Framework versions
 
-- Transformers 4.35.2
-- Pytorch 2.1.0+cu121
-- Datasets 2.16.1
-- Tokenizers 0.15.1
+- Transformers 4.40.1
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

runs/May01_20-51-07_6c6ca94f901c/events.out.tfevents.1714596756.6c6ca94f901c.200.0

@@ -1,3 +1,3 @@
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-size 9182
+oid sha256:a320892b5a44335900eff2e464532415cfc8a4a7e15482795ba0d0e939aad637
+size 9536