Initial Commit

README.md

@@ -1,4 +1,5 @@
 ---
+library_name: transformers
 license: mit
 base_model: microsoft/mdeberta-v3-base
 tags:
@@ -18,9 +19,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 5.3429
-- Accuracy: 0.4330
-- F1: 0.4179
+- Loss: 5.1657
+- Accuracy: 0.4577
+- F1: 0.4543
 
 ## Model description
 
@@ -49,30 +50,30 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| No log        | 1.72  | 100  | 1.1160          | 0.4074   | 0.3433 |
-| No log        | 3.45  | 200  | 1.2658          | 0.4149   | 0.3707 |
-| No log        | 5.17  | 300  | 1.7230          | 0.4599   | 0.4582 |
-| No log        | 6.9   | 400  | 1.7742          | 0.4383   | 0.4266 |
-| 0.6464        | 8.62  | 500  | 2.4181          | 0.4334   | 0.4215 |
-| 0.6464        | 10.34 | 600  | 2.9688          | 0.4444   | 0.4397 |
-| 0.6464        | 12.07 | 700  | 3.2008          | 0.4374   | 0.4342 |
-| 0.6464        | 13.79 | 800  | 4.2300          | 0.4233   | 0.4012 |
-| 0.6464        | 15.52 | 900  | 4.2439          | 0.4414   | 0.4382 |
-| 0.0996        | 17.24 | 1000 | 4.6596          | 0.4506   | 0.4385 |
-| 0.0996        | 18.97 | 1100 | 4.7742          | 0.4343   | 0.4252 |
-| 0.0996        | 20.69 | 1200 | 4.9060          | 0.4440   | 0.4336 |
-| 0.0996        | 22.41 | 1300 | 5.0117          | 0.4365   | 0.4288 |
-| 0.0996        | 24.14 | 1400 | 5.0594          | 0.4444   | 0.4348 |
-| 0.0222        | 25.86 | 1500 | 5.1602          | 0.4440   | 0.4351 |
-| 0.0222        | 27.59 | 1600 | 5.2402          | 0.4405   | 0.4325 |
-| 0.0222        | 29.31 | 1700 | 5.3429          | 0.4330   | 0.4179 |
+| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
+| No log        | 1.7241  | 100  | 1.1068          | 0.4330   | 0.3826 |
+| No log        | 3.4483  | 200  | 1.4495          | 0.4533   | 0.4238 |
+| No log        | 5.1724  | 300  | 1.5295          | 0.4586   | 0.4497 |
+| No log        | 6.8966  | 400  | 2.0122          | 0.4537   | 0.4516 |
+| 0.5768        | 8.6207  | 500  | 3.0885          | 0.4493   | 0.4417 |
+| 0.5768        | 10.3448 | 600  | 3.3878          | 0.4541   | 0.4497 |
+| 0.5768        | 12.0690 | 700  | 3.4115          | 0.4586   | 0.4564 |
+| 0.5768        | 13.7931 | 800  | 3.8779          | 0.4590   | 0.4572 |
+| 0.5768        | 15.5172 | 900  | 4.1514          | 0.4590   | 0.4579 |
+| 0.0737        | 17.2414 | 1000 | 4.6699          | 0.4462   | 0.4281 |
+| 0.0737        | 18.9655 | 1100 | 4.6724          | 0.4608   | 0.4612 |
+| 0.0737        | 20.6897 | 1200 | 4.6790          | 0.4603   | 0.4562 |
+| 0.0737        | 22.4138 | 1300 | 4.9305          | 0.4581   | 0.4564 |
+| 0.0737        | 24.1379 | 1400 | 5.0621          | 0.4568   | 0.4503 |
+| 0.0099        | 25.8621 | 1500 | 5.0787          | 0.4608   | 0.4574 |
+| 0.0099        | 27.5862 | 1600 | 5.1428          | 0.4581   | 0.4549 |
+| 0.0099        | 29.3103 | 1700 | 5.1657          | 0.4577   | 0.4543 |
 
 
 ### Framework versions
 
-- Transformers 4.33.3
+- Transformers 4.44.2
 - Pytorch 2.1.1+cu121
 - Datasets 2.14.5
-- Tokenizers 0.13.3
+- Tokenizers 0.19.1

config.json

@@ -39,7 +39,7 @@
   "relative_attention": true,
   "share_att_key": true,
   "torch_dtype": "float32",
-  "transformers_version": "4.33.3",
+  "transformers_version": "4.44.2",
   "type_vocab_size": 0,
   "vocab_size": 251000
 }

eval_results_cardiff.json

@@ -0,0 +1 @@
+{"arabic": {"f1": 0.48707540389654164, "accuracy": 0.4862068965517241, "confusion_matrix": [[159, 97, 34], [105, 123, 62], [91, 58, 141]]}, "english": {"f1": 0.579978194354665, "accuracy": 0.5781609195402299, "confusion_matrix": [[197, 78, 15], [103, 139, 48], [35, 88, 167]]}, "french": {"f1": 0.4161104946790835, "accuracy": 0.44022988505747124, "confusion_matrix": [[149, 114, 27], [65, 182, 43], [102, 136, 52]]}, "german": {"f1": 0.49275962433716414, "accuracy": 0.5, "confusion_matrix": [[97, 113, 80], [48, 172, 70], [40, 84, 166]]}, "hindi": {"f1": 0.4615527004195401, "accuracy": 0.4666666666666667, "confusion_matrix": [[96, 108, 86], [63, 158, 69], [52, 86, 152]]}, "italian": {"f1": 0.5166065385724214, "accuracy": 0.5160919540229885, "confusion_matrix": [[139, 108, 43], [46, 171, 73], [51, 100, 139]]}, "portuguese": {"f1": 0.42506022985325814, "accuracy": 0.42873563218390803, "confusion_matrix": [[97, 128, 65], [57, 162, 71], [42, 134, 114]]}, "spanish": {"f1": 0.5039475363264437, "accuracy": 0.503448275862069, "confusion_matrix": [[148, 91, 51], [96, 127, 67], [51, 76, 163]]}, "all": {"f1": 0.4962067776821599, "accuracy": 0.49525862068965515, "confusion_matrix": [[1119, 807, 394], [603, 1226, 491], [458, 760, 1102]]}}

model.safetensors

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+size 946716948

training_args.bin

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