Upload 15 files

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+Menta/tokenizer.json filter=lfs diff=lfs merge=lfs -text

Menta/README.md

@@ -0,0 +1,207 @@
+---
+base_model: Qwen/Qwen3-4B-Instruct-2507
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:Qwen/Qwen3-4B-Instruct-2507
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.17.1

Menta/adapter_config.json

@@ -0,0 +1,39 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen3-4B-Instruct-2507",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "k_proj",
+    "o_proj",
+    "v_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

Menta/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cf8e61c7f44e72367d974a04334ce0006272604694d77c7d7c5379cb69a0e43e
+size 23631240

Menta/added_tokens.json

@@ -0,0 +1,28 @@
+{
+  "</think>": 151668,
+  "</tool_call>": 151658,
+  "</tool_response>": 151666,
+  "<think>": 151667,
+  "<tool_call>": 151657,
+  "<tool_response>": 151665,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
+  "<|fim_pad|>": 151662,
+  "<|fim_prefix|>": 151659,
+  "<|fim_suffix|>": 151661,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644,
+  "<|image_pad|>": 151655,
+  "<|object_ref_end|>": 151647,
+  "<|object_ref_start|>": 151646,
+  "<|quad_end|>": 151651,
+  "<|quad_start|>": 151650,
+  "<|repo_name|>": 151663,
+  "<|video_pad|>": 151656,
+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
+  "<|vision_start|>": 151652
+}

Menta/chat_template.jinja

@@ -0,0 +1,61 @@
+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if message.content is string %}
+        {%- set content = message.content %}
+    {%- else %}
+        {%- set content = '' %}
+    {%- endif %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

Menta/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:06b50f881d2ee07e9280ebb8f6cd0246b8850d2f3f3f1abec2d6c73521f3795b
+size 47427979

Menta/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:788ea5a4e5b3f751353072a844c13567d8cb7fd2256239a2c817180d43be5ce9
+size 14645

Menta/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a6cfa1b0a6cbc14b460ef3b255c1c98a8d3516a97fdf7e2ce228a615aee28cd0
+size 1465

Menta/special_tokens_map.json

@@ -0,0 +1,31 @@
+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

Menta/tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:574de68a0f63f2004784a421c7d42c2b2786c05cb38542d2ed3525757a1f7fde
+size 11422932

Menta/tokenizer_config.json

@@ -0,0 +1,239 @@
+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
+      "content": "<|object_ref_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|object_ref_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151648": {
+      "content": "<|box_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151649": {
+      "content": "<|box_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151665": {
+      "content": "<tool_response>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151666": {
+      "content": "</tool_response>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151667": {
+      "content": "<think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151668": {
+      "content": "</think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 1010000,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}

Menta/trainer_state.json

@@ -0,0 +1,449 @@
+{
+  "best_global_step": 3000,
+  "best_metric": 2.048635482788086,
+  "best_model_checkpoint": "./qwen3_lora_multitask_output_logprob/config_1/checkpoint-3000",
+  "epoch": 3.0,
+  "eval_steps": 500,
+  "global_step": 4968,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.06038647342995169,
+      "grad_norm": 0.7042117714881897,
+      "learning_rate": 0.000495,
+      "loss": 2.5543,
+      "step": 100
+    },
+    {
+      "epoch": 0.12077294685990338,
+      "grad_norm": 0.683829128742218,
+      "learning_rate": 0.0004898315529991783,
+      "loss": 2.1273,
+      "step": 200
+    },
+    {
+      "epoch": 0.18115942028985507,
+      "grad_norm": 0.7821890115737915,
+      "learning_rate": 0.0004795603944124897,
+      "loss": 2.1013,
+      "step": 300
+    },
+    {
+      "epoch": 0.24154589371980675,
+      "grad_norm": 0.7839072942733765,
+      "learning_rate": 0.0004692892358258012,
+      "loss": 2.1201,
+      "step": 400
+    },
+    {
+      "epoch": 0.30193236714975846,
+      "grad_norm": 0.6462593674659729,
+      "learning_rate": 0.0004590180772391126,
+      "loss": 2.0848,
+      "step": 500
+    },
+    {
+      "epoch": 0.30193236714975846,
+      "eval_loss": 2.0794577598571777,
+      "eval_runtime": 45.4355,
+      "eval_samples_per_second": 16.177,
+      "eval_steps_per_second": 4.05,
+      "step": 500
+    },
+    {
+      "epoch": 0.36231884057971014,
+      "grad_norm": 1.08709716796875,
+      "learning_rate": 0.000448746918652424,
+      "loss": 2.0871,
+      "step": 600
+    },
+    {
+      "epoch": 0.4227053140096618,
+      "grad_norm": 0.8491250872612,
+      "learning_rate": 0.0004384757600657354,
+      "loss": 2.069,
+      "step": 700
+    },
+    {
+      "epoch": 0.4830917874396135,
+      "grad_norm": 0.8505752682685852,
+      "learning_rate": 0.0004282046014790468,
+      "loss": 2.1031,
+      "step": 800
+    },
+    {
+      "epoch": 0.5434782608695652,
+      "grad_norm": 0.8747426271438599,
+      "learning_rate": 0.00041793344289235826,
+      "loss": 2.0675,
+      "step": 900
+    },
+    {
+      "epoch": 0.6038647342995169,
+      "grad_norm": 0.8112818002700806,
+      "learning_rate": 0.0004076622843056697,
+      "loss": 2.035,
+      "step": 1000
+    },
+    {
+      "epoch": 0.6038647342995169,
+      "eval_loss": 2.064408540725708,
+      "eval_runtime": 45.3258,
+      "eval_samples_per_second": 16.216,
+      "eval_steps_per_second": 4.06,
+      "step": 1000
+    },
+    {
+      "epoch": 0.6642512077294686,
+      "grad_norm": 0.8023479580879211,
+      "learning_rate": 0.0003973911257189811,
+      "loss": 2.0594,
+      "step": 1100
+    },
+    {
+      "epoch": 0.7246376811594203,
+      "grad_norm": 0.9348495602607727,
+      "learning_rate": 0.00038711996713229255,
+      "loss": 1.9706,
+      "step": 1200
+    },
+    {
+      "epoch": 0.785024154589372,
+      "grad_norm": 0.8656277060508728,
+      "learning_rate": 0.00037684880854560394,
+      "loss": 2.0194,
+      "step": 1300
+    },
+    {
+      "epoch": 0.8454106280193237,
+      "grad_norm": 0.899181067943573,
+      "learning_rate": 0.00036657764995891534,
+      "loss": 2.0178,
+      "step": 1400
+    },
+    {
+      "epoch": 0.9057971014492754,
+      "grad_norm": 0.9141527414321899,
+      "learning_rate": 0.0003563064913722268,
+      "loss": 2.0371,
+      "step": 1500
+    },
+    {
+      "epoch": 0.9057971014492754,
+      "eval_loss": 2.055431365966797,
+      "eval_runtime": 45.3915,
+      "eval_samples_per_second": 16.192,
+      "eval_steps_per_second": 4.054,
+      "step": 1500
+    },
+    {
+      "epoch": 0.966183574879227,
+      "grad_norm": 1.0180304050445557,
+      "learning_rate": 0.00034603533278553824,
+      "loss": 2.0254,
+      "step": 1600
+    },
+    {
+      "epoch": 1.0265700483091786,
+      "grad_norm": 1.0414997339248657,
+      "learning_rate": 0.00033576417419884963,
+      "loss": 1.9749,
+      "step": 1700
+    },
+    {
+      "epoch": 1.0869565217391304,
+      "grad_norm": 1.15347421169281,
+      "learning_rate": 0.00032549301561216103,
+      "loss": 1.7882,
+      "step": 1800
+    },
+    {
+      "epoch": 1.1473429951690821,
+      "grad_norm": 1.247313141822815,
+      "learning_rate": 0.0003152218570254725,
+      "loss": 1.8447,
+      "step": 1900
+    },
+    {
+      "epoch": 1.2077294685990339,
+      "grad_norm": 1.1481050252914429,
+      "learning_rate": 0.0003049506984387839,
+      "loss": 1.8997,
+      "step": 2000
+    },
+    {
+      "epoch": 1.2077294685990339,
+      "eval_loss": 2.066617727279663,
+      "eval_runtime": 45.5973,
+      "eval_samples_per_second": 16.119,
+      "eval_steps_per_second": 4.035,
+      "step": 2000
+    },
+    {
+      "epoch": 1.2681159420289856,
+      "grad_norm": 1.1704497337341309,
+      "learning_rate": 0.0002946795398520953,
+      "loss": 1.8558,
+      "step": 2100
+    },
+    {
+      "epoch": 1.3285024154589373,
+      "grad_norm": 1.0295543670654297,
+      "learning_rate": 0.00028440838126540677,
+      "loss": 1.8212,
+      "step": 2200
+    },
+    {
+      "epoch": 1.3888888888888888,
+      "grad_norm": 1.4280544519424438,
+      "learning_rate": 0.00027413722267871816,
+      "loss": 1.8536,
+      "step": 2300
+    },
+    {
+      "epoch": 1.4492753623188406,
+      "grad_norm": 1.1617194414138794,
+      "learning_rate": 0.00026386606409202956,
+      "loss": 1.8502,
+      "step": 2400
+    },
+    {
+      "epoch": 1.5096618357487923,
+      "grad_norm": 1.466346025466919,
+      "learning_rate": 0.000253594905505341,
+      "loss": 1.8248,
+      "step": 2500
+    },
+    {
+      "epoch": 1.5096618357487923,
+      "eval_loss": 2.058035135269165,
+      "eval_runtime": 45.564,
+      "eval_samples_per_second": 16.131,
+      "eval_steps_per_second": 4.038,
+      "step": 2500
+    },
+    {
+      "epoch": 1.5700483091787438,
+      "grad_norm": 1.2693666219711304,
+      "learning_rate": 0.0002433237469186524,
+      "loss": 1.8562,
+      "step": 2600
+    },
+    {
+      "epoch": 1.6304347826086958,
+      "grad_norm": 1.1814815998077393,
+      "learning_rate": 0.00023305258833196385,
+      "loss": 1.7981,
+      "step": 2700
+    },
+    {
+      "epoch": 1.6908212560386473,
+      "grad_norm": 1.3537830114364624,
+      "learning_rate": 0.00022278142974527527,
+      "loss": 1.8252,
+      "step": 2800
+    },
+    {
+      "epoch": 1.751207729468599,
+      "grad_norm": 1.2975963354110718,
+      "learning_rate": 0.0002125102711585867,
+      "loss": 1.7719,
+      "step": 2900
+    },
+    {
+      "epoch": 1.8115942028985508,
+      "grad_norm": 1.5528435707092285,
+      "learning_rate": 0.00020223911257189812,
+      "loss": 1.7948,
+      "step": 3000
+    },
+    {
+      "epoch": 1.8115942028985508,
+      "eval_loss": 2.048635482788086,
+      "eval_runtime": 45.5817,
+      "eval_samples_per_second": 16.125,
+      "eval_steps_per_second": 4.037,
+      "step": 3000
+    },
+    {
+      "epoch": 1.8719806763285023,
+      "grad_norm": 1.17332124710083,
+      "learning_rate": 0.00019196795398520951,
+      "loss": 1.7871,
+      "step": 3100
+    },
+    {
+      "epoch": 1.9323671497584543,
+      "grad_norm": 1.4665601253509521,
+      "learning_rate": 0.00018169679539852096,
+      "loss": 1.7505,
+      "step": 3200
+    },
+    {
+      "epoch": 1.9927536231884058,
+      "grad_norm": 1.540218472480774,
+      "learning_rate": 0.00017142563681183238,
+      "loss": 1.7851,
+      "step": 3300
+    },
+    {
+      "epoch": 2.0531400966183573,
+      "grad_norm": 1.7435839176177979,
+      "learning_rate": 0.00016115447822514378,
+      "loss": 1.627,
+      "step": 3400
+    },
+    {
+      "epoch": 2.1135265700483092,
+      "grad_norm": 1.6157972812652588,
+      "learning_rate": 0.00015088331963845523,
+      "loss": 1.4929,
+      "step": 3500
+    },
+    {
+      "epoch": 2.1135265700483092,
+      "eval_loss": 2.0852222442626953,
+      "eval_runtime": 45.5366,
+      "eval_samples_per_second": 16.141,
+      "eval_steps_per_second": 4.041,
+      "step": 3500
+    },
+    {
+      "epoch": 2.1739130434782608,
+      "grad_norm": 1.6053498983383179,
+      "learning_rate": 0.00014061216105176662,
+      "loss": 1.5793,
+      "step": 3600
+    },
+    {
+      "epoch": 2.2342995169082127,
+      "grad_norm": 1.8563237190246582,
+      "learning_rate": 0.00013034100246507807,
+      "loss": 1.6087,
+      "step": 3700
+    },
+    {
+      "epoch": 2.2946859903381642,
+      "grad_norm": 1.5959372520446777,
+      "learning_rate": 0.00012006984387838948,
+      "loss": 1.5558,
+      "step": 3800
+    },
+    {
+      "epoch": 2.355072463768116,
+      "grad_norm": 1.7335354089736938,
+      "learning_rate": 0.0001097986852917009,
+      "loss": 1.5653,
+      "step": 3900
+    },
+    {
+      "epoch": 2.4154589371980677,
+      "grad_norm": 1.939560890197754,
+      "learning_rate": 9.952752670501234e-05,
+      "loss": 1.5306,
+      "step": 4000
+    },
+    {
+      "epoch": 2.4154589371980677,
+      "eval_loss": 2.0776526927948,
+      "eval_runtime": 45.5747,
+      "eval_samples_per_second": 16.127,
+      "eval_steps_per_second": 4.037,
+      "step": 4000
+    },
+    {
+      "epoch": 2.475845410628019,
+      "grad_norm": 1.7609752416610718,
+      "learning_rate": 8.925636811832375e-05,
+      "loss": 1.5559,
+      "step": 4100
+    },
+    {
+      "epoch": 2.536231884057971,
+      "grad_norm": 1.9164323806762695,
+      "learning_rate": 7.898520953163517e-05,
+      "loss": 1.5846,
+      "step": 4200
+    },
+    {
+      "epoch": 2.5966183574879227,
+      "grad_norm": 2.058566093444824,
+      "learning_rate": 6.871405094494659e-05,
+      "loss": 1.5144,
+      "step": 4300
+    },
+    {
+      "epoch": 2.6570048309178746,
+      "grad_norm": 2.0145790576934814,
+      "learning_rate": 5.8442892358258013e-05,
+      "loss": 1.5349,
+      "step": 4400
+    },
+    {
+      "epoch": 2.717391304347826,
+      "grad_norm": 1.6486459970474243,
+      "learning_rate": 4.8171733771569435e-05,
+      "loss": 1.5616,
+      "step": 4500
+    },
+    {
+      "epoch": 2.717391304347826,
+      "eval_loss": 2.0784645080566406,
+      "eval_runtime": 45.5266,
+      "eval_samples_per_second": 16.144,
+      "eval_steps_per_second": 4.042,
+      "step": 4500
+    },
+    {
+      "epoch": 2.7777777777777777,
+      "grad_norm": 2.2725300788879395,
+      "learning_rate": 3.790057518488085e-05,
+      "loss": 1.5013,
+      "step": 4600
+    },
+    {
+      "epoch": 2.838164251207729,
+      "grad_norm": 1.4655210971832275,
+      "learning_rate": 2.762941659819228e-05,
+      "loss": 1.4814,
+      "step": 4700
+    },
+    {
+      "epoch": 2.898550724637681,
+      "grad_norm": 1.7279577255249023,
+      "learning_rate": 1.7358258011503698e-05,
+      "loss": 1.5341,
+      "step": 4800
+    },
+    {
+      "epoch": 2.958937198067633,
+      "grad_norm": 2.0700881481170654,
+      "learning_rate": 7.087099424815119e-06,
+      "loss": 1.543,
+      "step": 4900
+    }
+  ],
+  "logging_steps": 100,
+  "max_steps": 4968,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 3,
+  "save_steps": 500,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": true
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 2.2210720529330995e+17,
+  "train_batch_size": 4,
+  "trial_name": null,
+  "trial_params": null
+}

Menta/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2e830292fc1cbf30fafebaa7e779e51f1bfa8482097117c3bf9dd4db908b3a6e
+size 5841