Training in progress, epoch 1

README.md

@@ -1,24 +1,25 @@
 ---
+library_name: transformers
 license: mit
-base_model: roberta-base
+base_model: roberta-large
 tags:
 - generated_from_trainer
 model-index:
-- name: Depression_continuous
+- name: Anger_continuous
   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. -->
 
-# Depression_continuous
+# Anger_continuous
 
-This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
+This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0702
-- Rmse: 0.2650
-- Mae: 0.2184
-- Corr: 0.4684
+- Loss: 0.0603
+- Rmse: 0.2455
+- Mae: 0.2029
+- Corr: 0.2745
 
 ## Model description
 
@@ -49,13 +50,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Rmse   | Mae    | Corr   |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
-| No log        | 1.0   | 268  | 0.0706          | 0.2657 | 0.2198 | 0.4565 |
-| 0.0718        | 2.0   | 536  | 0.0702          | 0.2650 | 0.2184 | 0.4684 |
+| No log        | 1.0   | 268  | 0.0575          | 0.2398 | 0.1984 | 0.2508 |
+| 0.0807        | 2.0   | 536  | 0.0603          | 0.2455 | 0.2029 | 0.2745 |
 
 
 ### Framework versions
 
-- Transformers 4.43.3
-- Pytorch 2.4.0
-- Datasets 2.20.0
+- Transformers 4.44.1
+- Pytorch 1.11.0
+- Datasets 2.12.0
 - Tokenizers 0.19.1

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "roberta-base",
+  "_name_or_path": "roberta-large",
   "architectures": [
     "RobertaForSequenceClassification"
   ],
@@ -9,25 +9,25 @@
   "eos_token_id": 2,
   "hidden_act": "gelu",
   "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
+  "hidden_size": 1024,
   "id2label": {
     "0": "LABEL_0"
   },
   "initializer_range": 0.02,
-  "intermediate_size": 3072,
+  "intermediate_size": 4096,
   "label2id": {
     "LABEL_0": 0
   },
   "layer_norm_eps": 1e-05,
   "max_position_embeddings": 514,
   "model_type": "roberta",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
   "pad_token_id": 1,
   "position_embedding_type": "absolute",
   "problem_type": "regression",
   "torch_dtype": "float32",
-  "transformers_version": "4.43.3",
+  "transformers_version": "4.44.1",
   "type_vocab_size": 1,
   "use_cache": true,
   "vocab_size": 50265

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:cac8fa9887f6e68767023656a0bb5c5785ba6befd729d557035ac0a2f069df4f
-size 498609748
+oid sha256:37b98f10b788d1110e670f394c87c8be04f57c11e734b585fccfcf43a6172889
+size 1421491316

training_args.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6a9d30c52ef5e169b03f10a80125b75ec0b555bbff92f61c7bd485ccc5c95b99
-size 5240
+oid sha256:dc2a0b31882f16af4141c30f412ccf229c4e2a646723df6fad88143c118a3d65
+size 4719