intent-recog

README.md

@@ -8,7 +8,6 @@ metrics:
 model-index:
 - name: intent-recog
   results: []
-pipeline_tag: text-classification
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -18,7 +17,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0003
+- Loss: 0.0005
 - F1: 1.0000
 
 ## Model description
@@ -50,12 +49,12 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step  | Validation Loss | F1     |
 |:-------------:|:-----:|:-----:|:---------------:|:------:|
-| 0.001         | 1.0   | 10464 | 0.0003          | 1.0000 |
+| 0.0077        | 1.0   | 10471 | 0.0005          | 1.0000 |
 
 
 ### Framework versions
 
-- Transformers 4.32.1
+- Transformers 4.33.1
 - Pytorch 2.0.1+cu118
-- Datasets 2.14.4
-- Tokenizers 0.13.3
+- Datasets 2.14.5
+- Tokenizers 0.13.3

config.json

@@ -13,14 +13,20 @@
   "id2label": {
     "0": "Replace",
     "1": "Order",
-    "2": "Cancel"
+    "2": "Cancel",
+    "3": "info",
+    "4": "update",
+    "5": "payement"
   },
   "initializer_range": 0.02,
   "intermediate_size": 3072,
   "label2id": {
     "Cancel": 2,
     "Order": 1,
-    "Replace": 0
+    "Replace": 0,
+    "info": 3,
+    "payement": 5,
+    "update": 4
   },
   "layer_norm_eps": 1e-05,
   "max_position_embeddings": 514,
@@ -31,7 +37,7 @@
   "pad_token_id": 1,
   "position_embedding_type": "absolute",
   "torch_dtype": "float32",
-  "transformers_version": "4.32.1",
+  "transformers_version": "4.33.1",
   "type_vocab_size": 1,
   "use_cache": true,
   "vocab_size": 250002

pytorch_model.bin

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training_args.bin

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