End of training

README.md

@@ -6,26 +6,26 @@ tags:
 metrics:
 - accuracy
 model-index:
-- name: xlm-roberta-large-xnli-anli
+- name: xlm-roberta-large-xnli-anli-v2.0
   results: []
 ---
 
 <!-- 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. -->
 
-# xlm-roberta-large-xnli-anli
+# xlm-roberta-large-xnli-anli-v2.0
 
 This model is a fine-tuned version of [vicgalle/xlm-roberta-large-xnli-anli](https://huggingface.co/vicgalle/xlm-roberta-large-xnli-anli) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3689
-- F1 Macro: 0.8721
-- F1 Micro: 0.8729
-- Accuracy Balanced: 0.8725
-- Accuracy: 0.8729
-- Precision Macro: 0.8718
-- Recall Macro: 0.8725
-- Precision Micro: 0.8729
-- Recall Micro: 0.8729
+- Loss: 0.3375
+- F1 Macro: 0.8802
+- F1 Micro: 0.8809
+- Accuracy Balanced: 0.8798
+- Accuracy: 0.8809
+- Precision Macro: 0.8808
+- Recall Macro: 0.8798
+- Precision Micro: 0.8809
+- Recall Micro: 0.8809
 
 ## Model description
 
@@ -77,24 +77,6 @@ The following hyperparameters were used during training:
 | 0.1909        | 2.71  | 3200 | 0.3777          | 0.8686   | 0.8698   | 0.8682            | 0.8698   | 0.8691          | 0.8682       | 0.8698          | 0.8698       |
 | 0.2021        | 2.88  | 3400 | 0.3685          | 0.8701   | 0.8708   | 0.8710            | 0.8708   | 0.8696          | 0.8710       | 0.8708          | 0.8708       |
 
-### eval result
-|Datasets|asadfgglie/nli-zh-tw-all/test|asadfgglie/BanBan_2024-10-17-facial_expressions-nli/test|eval_dataset|test_dataset|
-| :---: | :---: | :---: | :---: | :---: |
-|eval_loss|0.355|0.246|0.369|0.337|
-|eval_f1_macro|0.872|0.932|0.872|0.88|
-|eval_f1_micro|0.873|0.932|0.873|0.881|
-|eval_accuracy_balanced|0.872|0.932|0.873|0.88|
-|eval_accuracy|0.873|0.932|0.873|0.881|
-|eval_precision_macro|0.873|0.932|0.872|0.881|
-|eval_recall_macro|0.872|0.932|0.873|0.88|
-|eval_precision_micro|0.873|0.932|0.873|0.881|
-|eval_recall_micro|0.873|0.932|0.873|0.881|
-|eval_runtime|50.724|0.611|11.126|44.342|
-|eval_samples_per_second|167.574|1547.575|169.783|170.424|
-|eval_steps_per_second|2.622|24.539|2.696|2.684|
-|Size of dataset|8500|946|1889|7557|
-
-
 
 ### Framework versions
 

config.json

@@ -30,7 +30,7 @@
   "pad_token_id": 1,
   "position_embedding_type": "absolute",
   "problem_type": "single_label_classification",
-  "torch_dtype": "float32",
+  "torch_dtype": "float16",
   "transformers_version": "4.33.3",
   "type_vocab_size": 1,
   "use_cache": true,

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e63940481068b46f1865bf186fedad8ef12a3062d2e5d0b874ebe223eb4532b7
-size 2239705966
+oid sha256:781f6024d0d7c0f99b968b3b6458c2de26b985d4f99f286c6b6d6e64377dbdaf
+size 1119921006